Triple

T12897970
Position Surface form Disambiguated ID Type / Status
Subject S8 line E308542 entity
Predicate servesCity P82 FINISHED
Object Hanau E289017 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: Hanau | Statement: [S8 line, servesCity, Hanau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanau
Context triple: [S8 line, servesCity, Hanau]
  • A. Hanau chosen
    Hanau is a town in the German state of Hesse, known as an important regional center and the birthplace of the Brothers Grimm.
  • B. Benneckenstein
    Benneckenstein is a small town in central Germany located in the Harz mountain region, known for its scenic landscapes and outdoor recreation.
  • C. Hanworth
    Hanworth is a suburban residential area in west London, England, known for its parks, local amenities, and proximity to Heathrow Airport.
  • D. Meerbusch
    Meerbusch is a town in the German state of North Rhine-Westphalia, situated on the west bank of the Rhine near Düsseldorf and known for its affluent residential areas and green surroundings.
  • E. Poppenhausen
    Poppenhausen is a small German town located in the Schweinfurt administrative region of northern Bavaria.
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9717f3fc48190b61c8f6f36cd0725 completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0e54dc48190acf120ca5fe516ab completed May 3, 2026, 3:28 a.m.
Created at: April 9, 2026, 5:40 p.m.