Triple

T34500822
Position Surface form Disambiguated ID Type / Status
Subject The Gentleman from Arizona E885744 entity
Predicate title P38 FINISHED
Object The Gentleman from Arizona
"The Gentleman from Arizona" is a 1939 American Western film centered on an honorable Arizona rancher caught up in frontier conflicts and political intrigue.
E2099066 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: The Gentleman from Arizona | Statement: [The Gentleman from Arizona, title, The Gentleman from Arizona]
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: The Gentleman from Arizona
Triple: [The Gentleman from Arizona, title, The Gentleman from Arizona]
Generated description
"The Gentleman from Arizona" is a 1939 American Western film centered on an honorable Arizona rancher caught up in frontier conflicts and political intrigue.

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_69f349cc0220819081f154c6964f4dc2 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71f5208688190aff1e1dd867da7bb completed May 3, 2026, 10:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a372146ffc481909bf985bd0c9bbe96 completed June 20, 2026, 11:24 p.m.
NEDg Description generation batch_6a37224ef6188190915e0fd53d0949cc completed June 20, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a3722d05034819087a1399552af21cc completed June 20, 2026, 11:31 p.m.
Created at: May 1, 2026, 2:01 a.m.