Triple

T32245133
Position Surface form Disambiguated ID Type / Status
Subject The Jerusalem File E823724 entity
Predicate castMember P1668 FINISHED
Object Joseph O'Conor
Joseph O'Conor was an Irish-born British actor and playwright known for his work on stage, film, and television throughout the mid-20th century.
E2059921 NE FINISHED

How this triple was built (2 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: Joseph O'Conor | Statement: [The Jerusalem File, castMember, Joseph O'Conor]
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: Joseph O'Conor
Triple: [The Jerusalem File, castMember, Joseph O'Conor]
Generated description
Joseph O'Conor was an Irish-born British actor and playwright known for his work on stage, film, and television throughout the mid-20th century.

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_69f3490cdda88190a9d61e11252a771f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bc32ea2c8190b1cb870c14b05821 completed May 3, 2026, 3:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3611757790819091bb6574955d7764 completed June 20, 2026, 4:05 a.m.
NEDg Description generation batch_6a3612c356408190a73cad566383444d completed June 20, 2026, 4:10 a.m.
NED2 Entity disambiguation (via description) batch_6a36133940348190976ba1855cc33c37 completed June 20, 2026, 4:12 a.m.
Created at: May 1, 2026, 12:40 a.m.