Triple

T10721454
Position Surface form Disambiguated ID Type / Status
Subject Wendy Greene Bricmont E252830 entity
Predicate hasMiddleName P143 FINISHED
Object Greene E43976 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: Greene | Statement: [Wendy Greene Bricmont, hasMiddleName, Greene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greene
Context triple: [Wendy Greene Bricmont, hasMiddleName, Greene]
  • A. Greene chosen
    Greene is a common English surname borne by numerous notable figures in politics, the military, the arts, and other fields.
  • B. Eldridge
    Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
  • C. The Green
    The Green is a small rural settlement in Cumbria, England, situated near the town of Millom in the southwestern Lake District area.
  • D. The Green
    The Green is a historic central park and community gathering space located in downtown Morristown, New Jersey.
  • E. The Green
    The Green is a historic central public square in Dover, Delaware, known for its colonial-era buildings and role in early American political and civic life.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d70d43655081909b071100c96cb4f6 completed April 9, 2026, 2:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbb72b9ce08190a9134f3365d3f8cb completed April 12, 2026, 3:15 p.m.
Created at: April 8, 2026, 9:13 p.m.