Triple

T22087736
Position Surface form Disambiguated ID Type / Status
Subject Garret Mountain E545826 entity
Predicate hasPart P35 FINISHED
Object Lambert Castle 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: Lambert Castle | Statement: [Garret Mountain, hasPart, Lambert Castle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lambert Castle
Context triple: [Garret Mountain, hasPart, Lambert Castle]
  • A. Lambert Castle chosen
    Lambert Castle is a historic 19th-century mansion and museum in Paterson, New Jersey, known for its distinctive architecture and views over the surrounding area.
  • B. Valère Castle
    Valère Castle is a historic fortified complex overlooking the town of Sion in the Swiss canton of Valais, notable for its medieval architecture and hilltop basilica.
  • C. Lutry castle
    Lutry castle is a historic medieval fortress located in the town of Lutry on the shores of Lake Geneva in Switzerland.
  • D. Walferdange Castle
    Walferdange Castle is a historic Luxembourgish residence best known as the place where Prince Henry of the Netherlands died in 1879.
  • E. Champagne Castle
    Champagne Castle is a prominent mountain peak in South Africa’s Drakensberg range, known for its dramatic cliffs and popular hiking routes.
  • 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e3a98481908a7b3dc3f2a90276 completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.