Triple

T12566988
Position Surface form Disambiguated ID Type / Status
Subject Province of Westphalia E295497 entity
Predicate containsSettlement P847 FINISHED
Object Stadtallendorf E824431 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: Stadtallendorf | Statement: [Province of Westphalia, containsSettlement, Stadtallendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stadtallendorf
Context triple: [Province of Westphalia, containsSettlement, Stadtallendorf]
  • A. Stadtallendorf chosen
    Stadtallendorf is a town in the German state of Hesse known for its industrial history and role as a regional economic center.
  • B. Stadtoldendorf
    Stadtoldendorf is a small town in Lower Saxony, Germany, known for its location in the Weser Uplands and its historic half-timbered architecture.
  • C. Allendorf
    Allendorf is a village-level subdivision of the town of Sundern in the Hochsauerland district of North Rhine-Westphalia, Germany.
  • D. Aulendorf
    Aulendorf is a small town in the Upper Swabia region of southern Germany, known for its historic castle and spa facilities.
  • E. Hallerndorf
    Hallerndorf is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and traditional Franconian culture.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d954a325948190994bcfc9d571a3a8 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65eb71c548190826d243a354bd01c completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 11:49 p.m.