Triple

T14232268
Position Surface form Disambiguated ID Type / Status
Subject Strijp, Eindhoven E352779 entity
Predicate hasSubdivisions P747 FINISHED
Object Strijp-T E71265 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: Strijp-T | Statement: [Strijp, Eindhoven, hasSubdivisions, Strijp-T]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Strijp-T
Context triple: [Strijp, Eindhoven, hasSubdivisions, Strijp-T]
  • A. Strijp chosen
    Strijp is a district in the Dutch city of Eindhoven, historically known for its strong association with Philips and its transformation into a creative and cultural hub.
  • B. The Green Stripe
    The Green Stripe is a 1905 Fauvist portrait by Henri Matisse of his wife Amélie, notable for its bold use of a green line to divide and model the face.
  • C. Racing Stripes
    Racing Stripes is a 2005 family sports comedy film about a young zebra who dreams of becoming a racehorse.
  • D. Strijpen
    Strijpen is a village in East Flanders, Belgium, that forms part of the city of Zottegem.
  • E. Stikker
    Stikker is a surname most notably associated with Dirk Stikker, a Dutch politician and diplomat who served as NATO Secretary General.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de622cdd6481908befa179a9675bb5 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3251ec5881909fcebc9477d6a761 completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:07 a.m.