Triple

T9749689
Position Surface form Disambiguated ID Type / Status
Subject Rhine-Ruhr S-Bahn E236408 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: [Rhine-Ruhr S-Bahn, servesCity, Herne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herne
Context triple: [Rhine-Ruhr S-Bahn, servesCity, Herne]
  • A. Herne chosen
    Herne is a city in the Ruhr area of North Rhine-Westphalia, Germany, known for its industrial heritage and dense urban character.
  • B. 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.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f6a2f8c8190a6f6af6587ee90b8 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1b01678f88190900a941b9d111c58 completed April 5, 2026, 12:43 a.m.
Created at: March 30, 2026, 8:24 p.m.