Triple

T23509121
Position Surface form Disambiguated ID Type / Status
Subject The Girl of the Golden West (1938 film) E572367 entity
Predicate screenwriter P2831 FINISHED
Object Boyce DeGaw
Boyce DeGaw was a screenwriter active in early 20th-century American cinema, known for his work on the 1938 film adaptation of "The Girl of the Golden West."
E1610472 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: Boyce DeGaw | Statement: [The Girl of the Golden West (1938 film), screenwriter, Boyce DeGaw]
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: Boyce DeGaw
Triple: [The Girl of the Golden West (1938 film), screenwriter, Boyce DeGaw]
Generated description
Boyce DeGaw was a screenwriter active in early 20th-century American cinema, known for his work on the 1938 film adaptation of "The Girl of the Golden West."

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_69e245b5e4208190bac8a6509867e394 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a902c0788190840d7df1b5450b4d completed April 29, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75ed2b288190a0308290784ae994 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f77855e2c81909c3e92f499d134dc completed May 21, 2026, 9:22 p.m.
NED2 Entity disambiguation (via description) batch_6a0f790a4d648190b210725d44601bca completed May 21, 2026, 9:28 p.m.
Created at: April 17, 2026, 6:07 p.m.