Triple

T36329920
Position Surface form Disambiguated ID Type / Status
Subject Hooray for Tom E894614 entity
Predicate lyricist P1360 FINISHED
Object James Taylor
James Taylor is an American singer-songwriter and guitarist renowned for his introspective lyrics and mellow, folk-influenced soft rock hits such as "Fire and Rain" and "You've Got a Friend."
E45047 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: James Taylor | Statement: [Hooray for Tom, lyricist, James Taylor]
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: James Taylor
Triple: [Hooray for Tom, lyricist, James Taylor]
Generated description
James Taylor is an American singer-songwriter and guitarist renowned for his introspective lyrics and mellow, folk-influenced soft rock hits such as "Fire and Rain" and "You've Got a Friend."

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_69f76e4dcf088190a6c3216c209cab52 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7ba6dbad88190afd12b913fb8a720 completed May 3, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c3f87f1c81909be2dccfcff0e5e4 completed June 22, 2026, 11:23 p.m.
NEDg Description generation batch_6a39c58a9f1c81909266d4e572435c28 completed June 22, 2026, 11:30 p.m.
NED2 Entity disambiguation (via description) batch_6a39c63a49fc81909ba597caa07cdd68 completed June 22, 2026, 11:33 p.m.
Created at: May 3, 2026, 4:09 p.m.