Triple

T32631039
Position Surface form Disambiguated ID Type / Status
Subject Jennie Lew Tugend E834206 entity
Predicate notableWork P4 FINISHED
Object My Family
"My Family" is a 1995 American drama film that chronicles three generations of a Mexican-American family in Los Angeles, exploring themes of immigration, identity, and cultural heritage.
E1201205 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: My Family | Statement: [Jennie Lew Tugend, notableWork, My Family]
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: My Family
Triple: [Jennie Lew Tugend, notableWork, My Family]
Generated description
"My Family" is a 1995 American drama film that chronicles three generations of a Mexican-American family in Los Angeles, exploring themes of immigration, identity, and cultural heritage.

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_69f3492dc2308190a88c6e30a3f3f576 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c71dc18c819084998819b2934543 completed May 3, 2026, 3:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34929f5d448190a5d1fcf2bef8ff08 completed June 19, 2026, 12:51 a.m.
NEDg Description generation batch_6a34935caff8819097c46aa1de42eb95 completed June 19, 2026, 12:54 a.m.
NED2 Entity disambiguation (via description) batch_6a3493c4efb881909c333ffbe0642910 completed June 19, 2026, 12:56 a.m.
Created at: May 1, 2026, 1:07 a.m.