Triple

T33401316
Position Surface form Disambiguated ID Type / Status
Subject All the Real Girls E855304 entity
Predicate editor P1954 FINISHED
Object Steven Gonzales
Steven Gonzales is a film editor known for his work on independent films, including the drama "All the Real Girls."
E2106817 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: Steven Gonzales | Statement: [All the Real Girls, editor, Steven Gonzales]
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: Steven Gonzales
Triple: [All the Real Girls, editor, Steven Gonzales]
Generated description
Steven Gonzales is a film editor known for his work on independent films, including the drama "All the Real Girls."

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_69f3496e3f1c8190bcecfa82aa9d17ff completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e41576808190a7c24e328b045a14 completed May 3, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3748cd13e88190ad0544793a0b5eb3 completed June 21, 2026, 2:13 a.m.
NEDg Description generation batch_6a3749d08ff48190b252be336b564065 completed June 21, 2026, 2:17 a.m.
NED2 Entity disambiguation (via description) batch_6a374dbedf148190bc1b24d470fd2224 completed June 21, 2026, 2:34 a.m.
Created at: May 1, 2026, 1:35 a.m.