Triple

T4555642
Position Surface form Disambiguated ID Type / Status
Subject Draymond Green E120470 entity
Predicate familyName P18 FINISHED
Object Green E141909 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: Green | Statement: [Draymond Green, familyName, Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green
Context triple: [Draymond Green, familyName, Green]
  • A. Green chosen
    Green is a common English surname of Anglo-Saxon origin, typically derived from a descriptive nickname related to the color green or someone who lived near a village green.
  • B. Groen
    Groen is a Flemish green political party in Belgium known for its progressive stance on environmental and social issues.
  • C. Green, Green
    "Green, Green" is a 1963 folk song by The New Christy Minstrels that became one of their best-known hits and a staple of the American folk revival era.
  • D. Greens
    The Greens were one of the major chariot racing factions in ancient Rome, known for their passionate supporters and fierce rivalry with other teams such as the Blues.
  • E. Gelb
    Gelb is a surname most prominently associated with Peter Gelb, the influential general manager of the Metropolitan Opera in New York City.
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd5813af948190b10b02dadf6496bf completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc57d59f88190857cbda79caf3c38 completed March 20, 2026, 10:09 p.m.
Created at: March 20, 2026, 1:09 p.m.