Triple

T17115698
Position Surface form Disambiguated ID Type / Status
Subject Vaujours E415331 entity
Predicate borders P224 FINISHED
Object Courtry
Courtry is a small suburban commune in the Seine-Saint-Denis department in the northeastern outskirts of Paris, France.
 E1250891 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: Courtry | Statement: [Vaujours, borders, Courtry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Courtry
Context triple: [Vaujours, borders, Courtry]
  • A. Kurtoe
    Kurtoe is a traditional cultural region in northeastern Bhutan, known for its rich heritage and association with the historic Lhuentse area.
  • B. Tyner
    Tyner is the surname of renowned American jazz pianist and composer McCoy Tyner, closely associated with the John Coltrane Quartet and influential modal jazz recordings.
  • C. Tennin
    Tennin was a Japanese era name (nengō) of the late Heian period, used during the reign of Emperor Toba.
  • D. Mulroy
    Mulroy is a character from the film "The Terminal," known as one of the airport workers who befriends Viktor Navorski during his extended stay in the terminal.
  • E. Grier
    Grier is the surname of Pam Grier, an influential American actress renowned for her groundbreaking roles in 1970s blaxploitation films.
  • 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: Courtry
Triple: [Vaujours, borders, Courtry]
Generated description
Courtry is a small suburban commune in the Seine-Saint-Denis department in the northeastern outskirts of Paris, France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Courtry
Target entity description: Courtry is a small suburban commune in the Seine-Saint-Denis department in the northeastern outskirts of Paris, France.
  • A. Kurtoe
    Kurtoe is a traditional cultural region in northeastern Bhutan, known for its rich heritage and association with the historic Lhuentse area.
  • B. Tyner
    Tyner is the surname of renowned American jazz pianist and composer McCoy Tyner, closely associated with the John Coltrane Quartet and influential modal jazz recordings.
  • C. Tennin
    Tennin was a Japanese era name (nengō) of the late Heian period, used during the reign of Emperor Toba.
  • D. Mulroy
    Mulroy is a character from the film "The Terminal," known as one of the airport workers who befriends Viktor Navorski during his extended stay in the terminal.
  • E. Grier
    Grier is the surname of Pam Grier, an influential American actress renowned for her groundbreaking roles in 1970s blaxploitation films.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e80528588190a877dcc6d6d3a392 completed April 18, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a0957c081908a1902aea2f02d2a completed May 11, 2026, 2:08 a.m.
NEDg Description generation batch_6a013b749680819097159f0fdc379f2c completed May 11, 2026, 2:14 a.m.
NED2 Entity disambiguation (via description) batch_6a013bf9ef508190aac1155680f33eaf completed May 11, 2026, 2:16 a.m.
Created at: April 10, 2026, 5:35 a.m.