Triple

T26170756
Position Surface form Disambiguated ID Type / Status
Subject Coleman Report E654394 entity
Predicate coAuthor P398 FINISHED
Object Carol J. Hobson
Carol J. Hobson is an American researcher known for coauthoring the influential 1966 Coleman Report on educational equality and school effectiveness.
 E1768879 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: Carol J. Hobson | Statement: [Coleman Report, coAuthor, Carol J. Hobson]
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: Carol J. Hobson
Triple: [Coleman Report, coAuthor, Carol J. Hobson]
Generated description
Carol J. Hobson is an American researcher known for coauthoring the influential 1966 Coleman Report on educational equality and school effectiveness.

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_69ee5b44391c81908bdbd8813ba9aa99 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60c435d748190abc1b63303721551 completed May 2, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7a9be388190a77eb80df3b0f098 completed May 24, 2026, 7:24 a.m.
NEDg Description generation batch_6a12a8b8ec608190846c55dabeec801a completed May 24, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_6a12a951f04881909419d5b9d41d5c79 completed May 24, 2026, 7:31 a.m.
Created at: April 26, 2026, 8:35 p.m.