Triple

T14435148
Position Surface form Disambiguated ID Type / Status
Subject Herne port E357939 entity
Predicate servesCity P82 FINISHED
Object Herne E355366 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: Herne | Statement: [Herne port, servesCity, Herne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herne
Context triple: [Herne port, servesCity, Herne]
  • A. Herne
    Herne is a small Flemish municipality in the Belgian province of Flemish Brabant, known for its rural character and location in the Pajottenland region.
  • B. Herne chosen
    Herne is a city in the Ruhr area of North Rhine-Westphalia, Germany, known for its industrial heritage and dense urban character.
  • C. Harpur Hill
    Harpur Hill is a small village in the High Peak district of Derbyshire, England, known for its elevated position and proximity to the spa town of Buxton.
  • D. Herne Hill
    Herne Hill is a residential district in South London known for its Victorian architecture, local markets, and proximity to Brockwell Park.
  • E. Highgate Wood
    Highgate Wood is an ancient semi-natural woodland and public park in North London, known for its rich biodiversity, historic character, and recreational facilities.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9148cf4481909082cc91b2f76218 completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd648b8f348190be11645b371b4102 completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:18 a.m.