Triple

T14862606
Position Surface form Disambiguated ID Type / Status
Subject Morisset railway station E349534 entity
Predicate servedPlace P3936 FINISHED
Object Morisset E842604 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: Morisset | Statement: [Morisset railway station, servedPlace, Morisset]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morisset
Context triple: [Morisset railway station, servedPlace, Morisset]
  • A. Morisset chosen
    Morisset is a town in the City of Lake Macquarie, New South Wales, Australia, known as a regional centre near the southern end of Lake Macquarie.
  • B. Maincy
    Maincy is a commune in north-central France best known for encompassing the Château and Gardens of Vaux-le-Vicomte.
  • C. Missillac
    Missillac is a commune in western France’s Loire-Atlantique department, known for its rural character and historic Château de la Bretesche.
  • D. Mercy-le-Haut
    Mercy-le-Haut is a small commune in northeastern France, notable as the birthplace of former French president Albert Lebrun.
  • E. Muscoy
    Muscoy is an unincorporated community in San Bernardino County, California, known for its semi-rural character within the Inland Empire region.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded574d0ec8190a6afed672ba6c2f9 completed April 15, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe650c41b081909cdadbaec472eee3 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:54 a.m.