Triple

T30619296
Position Surface form Disambiguated ID Type / Status
Subject Abilene Town E779401 entity
Predicate producer P490 FINISHED
Object Jules Levey
Jules Levey was an American film producer active in the mid-20th century, known for overseeing a variety of Hollywood features across different genres.
 E1931614 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: Jules Levey | Statement: [Abilene Town, producer, Jules Levey]
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: Jules Levey
Triple: [Abilene Town, producer, Jules Levey]
Generated description
Jules Levey was an American film producer active in the mid-20th century, known for overseeing a variety of Hollywood features across different genres.

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_69f224a3307081909a6dca8ca75dbf48 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f689ed5b9c81909976d061f71d782a completed May 2, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b07b73b081908814d4be50b5dfc6 completed June 10, 2026, 12:31 a.m.
NEDg Description generation batch_6a28b474de208190b602fcb13061ce98 completed June 10, 2026, 12:48 a.m.
NED2 Entity disambiguation (via description) batch_6a28b54c10288190915b789c2f1b250d completed June 10, 2026, 12:52 a.m.
Created at: April 29, 2026, 8:26 p.m.