Triple

T4484135
Position Surface form Disambiguated ID Type / Status
Subject N57 E107194 entity
Predicate connects P390 FINISHED
Object Zuid-Holland E97222 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: Zuid-Holland | Statement: [N57, connects, Zuid-Holland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zuid-Holland
Context triple: [N57, connects, Zuid-Holland]
  • A. Zuid-Holland chosen
    Zuid-Holland is a densely populated coastal province in the western Netherlands that includes major cities such as Rotterdam and The Hague.
  • B. Gelderland
    Gelderland is a large province in the eastern Netherlands known for its varied landscapes, including the forested Veluwe region and the river areas along the Rhine, Waal, and IJssel.
  • C. North Holland
    North Holland is a province in the western Netherlands known for encompassing the national capital, Amsterdam, as well as historic towns and North Sea coastline.
  • D. Overijssel
    Overijssel is a province in the eastern Netherlands known for its historic Hanseatic cities, rivers, and varied landscapes of forests, heathlands, and farmland.
  • E. North Brabant
    North Brabant is a southern province of the Netherlands known for its historic cities, Catholic cultural heritage, and role as a key battleground during World War II.
  • 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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52a54c6c8190a7421bea6e3c00f1 completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c963dc62f88190b2aff49f5cb5fe27 completed March 29, 2026, 5:39 p.m.
Created at: March 20, 2026, 12:58 p.m.