Triple

T2878741
Position Surface form Disambiguated ID Type / Status
Subject Amélie E56943 entity
Predicate relatedName P3889 FINISHED
Object Emily
Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
 E315868 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: Emily | Statement: [Amélie, relatedName, Emily]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emily
Context triple: [Amélie, relatedName, Emily]
  • A. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • B. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • C. Jane
    Jane is a feminine given name of English origin that has been widely used in many English-speaking countries for centuries.
  • D. Amy
    Amy is a critically acclaimed 2015 documentary film about the life and career of British singer-songwriter Amy Winehouse.
  • E. Jessica
    Jessica Barth is an American actress best known for her comedic role as Tami-Lynn in the "Ted" film series.
  • 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: Emily
Triple: [Amélie, relatedName, Emily]
Generated description
Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emily
Target entity description: Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • A. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • B. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • C. Jane
    Jane is a feminine given name of English origin that has been widely used in many English-speaking countries for centuries.
  • D. Amy
    Amy is a critically acclaimed 2015 documentary film about the life and career of British singer-songwriter Amy Winehouse.
  • E. Jessica
    Jessica Barth is an American actress best known for her comedic role as Tami-Lynn in the "Ted" film series.
  • 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_69ab4a4ced288190ab6d3e062d10f7f6 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abe008925c81909683d0ebc6227e5e completed March 7, 2026, 8:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108cc4870819081e68032517468a8 completed March 11, 2026, 6:16 a.m.
NEDg Description generation batch_69b10b5c37ac81908ffc9ce949c86ec7 completed March 11, 2026, 6:27 a.m.
NED2 Entity disambiguation (via description) batch_69b10bdb450081909be83175a043043b completed March 11, 2026, 6:29 a.m.
Created at: March 6, 2026, 10:03 p.m.