Triple

T26682825
Position Surface form Disambiguated ID Type / Status
Subject Anne Shirley E672659 entity
Predicate notableWork P4 FINISHED
Object Three on a Match (1932 film)
Three on a Match (1932 film) is a pre-Code crime drama notable for its intertwined story of three women from childhood to adulthood and for featuring early performances by future star Anne Shirley.
E1734439 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: Three on a Match (1932 film) | Statement: [Anne Shirley, notableWork, Three on a Match (1932 film)]
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: Three on a Match (1932 film)
Triple: [Anne Shirley, notableWork, Three on a Match (1932 film)]
Generated description
Three on a Match (1932 film) is a pre-Code crime drama notable for its intertwined story of three women from childhood to adulthood and for featuring early performances by future star Anne Shirley.

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_69eecda13424819092b17942c4edf722 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6173afcd881908356903457eef60e completed May 2, 2026, 3:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec59c74c8190947ce4b5de6fb0d5 completed May 23, 2026, 6:05 p.m.
NEDg Description generation batch_6a11ed57baa8819090556b61b3ed4fdf completed May 23, 2026, 6:09 p.m.
NED2 Entity disambiguation (via description) batch_6a11ee05a1e08190a2828bc52ba17279 completed May 23, 2026, 6:12 p.m.
Created at: April 27, 2026, 3:21 a.m.