Triple

T17441369
Position Surface form Disambiguated ID Type / Status
Subject Furnace Green E424660 entity
Predicate adjacentTo P224 FINISHED
Object Tilgate NE NERFINISHED

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: Tilgate | Statement: [Furnace Green, adjacentTo, Tilgate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tilgate
Context triple: [Furnace Green, adjacentTo, Tilgate]
  • A. Tilgate chosen
    Tilgate is a residential neighbourhood and parkland area in the town of Crawley in West Sussex, England, known for Tilgate Park and its lakes and woodlands.
  • B. Tyssedal
    Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
  • C. Nadderud
    Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
  • D. Ottosdal
    Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
  • E. Vangsnes
    Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44ff75538819083f77756d39a1aaa completed April 19, 2026, 3:45 a.m.
Created at: April 10, 2026, 5:46 a.m.