Triple

T4126824
Position Surface form Disambiguated ID Type / Status
Subject Inverness railway station E92745 entity
Predicate locatedIn P40 FINISHED
Object Highland E4352 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: Highland | Statement: [Inverness railway station, locatedIn, Highland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Highland
Context triple: [Inverness railway station, locatedIn, Highland]
  • A. Highland
    Highland is a suburban city in Southern California’s Inland Empire, located in San Bernardino County near the city of San Bernardino.
  • B. Highlands region
    The Highlands region is a mountainous inland area of Papua New Guinea known for its rugged terrain, cool climate, and diverse traditional cultures.
  • C. Scottish Highlands chosen
    The Scottish Highlands are a rugged, sparsely populated region in northern Scotland known for their dramatic mountains, deep glens, lochs, and strong Gaelic cultural heritage.
  • D. Kutaisi Lowland
    Kutaisi Lowland is a fertile lowland region in western Georgia known for its agricultural significance and location along the middle course of the Rioni River.
  • E. Grampian
    Grampian was a former local government region in northeast Scotland, centered on the city of Aberdeen and known for its North Sea oil industry and agricultural hinterland.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af0219f0e48190b0a925f09d858d65 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576b96e588190bdf346a66a95138a completed March 14, 2026, 2:54 p.m.
Created at: March 9, 2026, 3:42 p.m.