Triple

T8527688
Position Surface form Disambiguated ID Type / Status
Subject Wilrijk E201858 entity
Predicate near P350 FINISHED
Object Hoboken district E335657 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: Hoboken district | Statement: [Wilrijk, near, Hoboken district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hoboken district
Context triple: [Wilrijk, near, Hoboken district]
  • A. West Hoboken, New Jersey
    West Hoboken, New Jersey was a former Hudson County municipality that was eventually consolidated into what is now Union City.
  • B. Hoboken
    Hoboken is a small New Jersey city across the Hudson River from Manhattan, known for its waterfront views, historic brownstones, and vibrant dining and nightlife scene.
  • C. Hoboken chosen
    Hoboken is a district of the Belgian city of Antwerp, known for its residential character and industrial areas along the Scheldt River.
  • D. Buena Borough, New Jersey
    Buena Borough, New Jersey is a small incorporated community in southern New Jersey known for its rural character and location within the Philadelphia metropolitan area.
  • E. North Bergen, New Jersey
    North Bergen, New Jersey is a densely populated township in northeastern New Jersey known for its steep Palisades terrain and proximity to New York City along the Hudson River.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6477100819081fa20cb6b8ea3d7 completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d54ef908190970a1010c8018abd completed April 2, 2026, 1:21 p.m.
Created at: March 30, 2026, 6:17 p.m.