Triple

T27192464
Position Surface form Disambiguated ID Type / Status
Subject Big Five personality traits E683510 entity
Predicate hasProponent P9868 FINISHED
Object Lewis Goldberg
Lewis Goldberg is an American personality psychologist known for his pioneering work in developing and promoting the Big Five (Five-Factor) model of personality.
E1760380 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: Lewis Goldberg | Statement: [Big Five personality traits, hasProponent, Lewis Goldberg]
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: Lewis Goldberg
Triple: [Big Five personality traits, hasProponent, Lewis Goldberg]
Generated description
Lewis Goldberg is an American personality psychologist known for his pioneering work in developing and promoting the Big Five (Five-Factor) model of personality.

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_69eefad140408190b8586fdebcf9af46 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625ac8e4c8190b44c30995739731f completed May 2, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a125395e7008190b35cb5184307bd3d completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a1254702dfc8190b32f5378eb7d81e0 completed May 24, 2026, 1:29 a.m.
NED2 Entity disambiguation (via description) batch_6a125512eb608190b958f82af3475535 completed May 24, 2026, 1:32 a.m.
Created at: April 27, 2026, 9:32 a.m.