Triple

T3365057
Position Surface form Disambiguated ID Type / Status
Subject Prentiss M. Brown E70815 entity
Predicate familyName P18 FINISHED
Object Brown E101694 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: Brown | Statement: [Prentiss M. Brown, familyName, Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brown
Context triple: [Prentiss M. Brown, familyName, Brown]
  • A. Brown chosen
    Brown is a common English-language surname of Anglo-Saxon origin, typically derived from a nickname referring to hair color, complexion, or clothing.
  • B. Maroon
    Maroon refers to the descendants of escaped African slaves in the Americas who formed independent communities, notably in places like Suriname and Jamaica, preserving distinct African-derived cultures and traditions.
  • C. Gray
    Gray is the commonly used short form of the name Gray Davis, the former governor of California.
  • D. Gray
    Gray is a historic commune in eastern France known for its picturesque setting along the Saône River and its well-preserved old town.
  • E. Gray
    Gray is a common English surname of Anglo-Saxon origin, often associated with families from Britain and Ireland.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb28643f48190b78b0222f8323344 completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3254daf8c8190b2141682503c111e completed March 12, 2026, 8:42 p.m.
Created at: March 8, 2026, 3:13 p.m.