Triple

T12173931
Position Surface form Disambiguated ID Type / Status
Subject Atiba Hutchinson E290040 entity
Predicate hasPlayedInCountry P10863 FINISHED
Object Netherlands E864 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: Netherlands | Statement: [Atiba Hutchinson, hasPlayedInCountry, Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Netherlands
Context triple: [Atiba Hutchinson, hasPlayedInCountry, Netherlands]
  • A. Netherlands chosen
    The Netherlands is a Western European country known for its low-lying geography, extensive canal systems, and historically significant role in global trade and European politics.
  • B. Holland
    Holland is a common English surname of Dutch origin, historically referring to people from the Holland region of the Netherlands.
  • C. Holland
    Holland is a historic coastal region in the western Netherlands that became the political and economic heartland of the emerging Dutch state.
  • D. Holland
    Holland is a regional less-than-truckload (LTL) freight carrier in the United States known for its operations in the Midwest and surrounding areas.
  • E. Holland
    Holland is a small settlement on the Orkney island of Stronsay in Scotland, known for its rural character and coastal surroundings.
  • 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915dab42881908e2580c631d4d1cf completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6366adc8190b5c8163af684afde completed May 2, 2026, 1:03 p.m.
Created at: April 8, 2026, 9:50 p.m.