Triple

T5387126
Position Surface form Disambiguated ID Type / Status
Subject Engadine E120227 entity
Predicate contains P35 FINISHED
Object Sent
Sent is a picturesque village in the Lower Engadine region of the Swiss canton of Graubünden, known for its traditional architecture and alpine setting.
 E515098 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sent | Statement: [Engadine, contains, Sent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sent
Context triple: [Engadine, contains, Sent]
  • A. Return to Sender
    "Return to Sender" is a young adult novel by Julia Alvarez that explores themes of immigration, family, and cultural identity through the story of a Vermont farm boy and the undocumented Mexican family working for his parents.
  • B. Mensagem
    Mensagem is a seminal poetry collection by Portuguese writer Fernando Pessoa that reflects on Portugal’s history, identity, and mythic destiny.
  • C. Received Text
    The Received Text, or Textus Receptus, is a historic printed Greek New Testament text that served as the primary basis for many early Protestant Bible translations, including the King James Version.
  • D. sns
    sns is the conventional alias used when importing Seaborn, a popular Python data visualization library built on top of Matplotlib.
  • E. SEP
    SEP is the Mexican federal government department responsible for overseeing and regulating the national education system.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sent
Triple: [Engadine, contains, Sent]
Generated description
Sent is a picturesque village in the Lower Engadine region of the Swiss canton of Graubünden, known for its traditional architecture and alpine setting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sent
Target entity description: Sent is a picturesque village in the Lower Engadine region of the Swiss canton of Graubünden, known for its traditional architecture and alpine setting.
  • A. Return to Sender
    "Return to Sender" is a young adult novel by Julia Alvarez that explores themes of immigration, family, and cultural identity through the story of a Vermont farm boy and the undocumented Mexican family working for his parents.
  • B. Mensagem
    Mensagem is a seminal poetry collection by Portuguese writer Fernando Pessoa that reflects on Portugal’s history, identity, and mythic destiny.
  • C. Received Text
    The Received Text, or Textus Receptus, is a historic printed Greek New Testament text that served as the primary basis for many early Protestant Bible translations, including the King James Version.
  • D. sns
    sns is the conventional alias used when importing Seaborn, a popular Python data visualization library built on top of Matplotlib.
  • E. SEP
    SEP is the Mexican federal government department responsible for overseeing and regulating the national education system.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69bd46354c648190a38b26f107010a96 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd86f8d81081909174027a4fe640f2 completed March 20, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf295542b08190849e48dbf826d9ec completed March 21, 2026, 11:27 p.m.
NEDg Description generation batch_69bf2a0aa4608190ad696442aa56dad5 completed March 21, 2026, 11:30 p.m.
NED2 Entity disambiguation (via description) batch_69bf2a64313881908d12d0c27a97927b completed March 21, 2026, 11:31 p.m.
Created at: March 20, 2026, 2:03 p.m.