Triple

T35911252
Position Surface form Disambiguated ID Type / Status
Subject Conway Tearle E1038615 entity
Predicate notableWork P4 FINISHED
Object The Way of a Woman
The Way of a Woman is a silent-era film associated with actor-director Conway Tearle, reflecting early 20th-century American melodramatic cinema.
 E2161302 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 Way of a Woman | Statement: [Conway Tearle, notableWork, The Way of a Woman]
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 Way of a Woman
Triple: [Conway Tearle, notableWork, The Way of a Woman]
Generated description
The Way of a Woman is a silent-era film associated with actor-director Conway Tearle, reflecting early 20th-century American melodramatic cinema.

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_69f76e2259608190bf6788a132e0d139 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aaa2525081909a333b254f7059c6 completed May 3, 2026, 8:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae2defc88190b9fcf64b19a17408 completed June 22, 2026, 3:38 a.m.
NEDg Description generation batch_6a38aec1b6508190a3bc1151af839daa completed June 22, 2026, 3:40 a.m.
NED2 Entity disambiguation (via description) batch_6a38af52e8288190abf63800ab6ce010 completed June 22, 2026, 3:43 a.m.
Created at: May 3, 2026, 4:07 p.m.