Triple

T13635398
Position Surface form Disambiguated ID Type / Status
Subject Weiningen E325834 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Unterengstringen E317798 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: Unterengstringen | Statement: [Weiningen, hasNeighboringMunicipality, Unterengstringen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unterengstringen
Context triple: [Weiningen, hasNeighboringMunicipality, Unterengstringen]
  • A. Unterengstringen chosen
    Unterengstringen is a small municipality in the canton of Zurich in northern Switzerland, situated along the Limmat River near the city of Zurich.
  • B. Untermetten
    Untermetten is a locality or district that forms part of the municipality of Metten in Bavaria, Germany.
  • C. Dettenschwang
    Dettenschwang is a village and district of the market town Dießen am Ammersee in the Bavarian region of Germany.
  • D. الخيط الرفيع
    الخيط الرفيع هو فيلم دراما مصري شهير من أوائل السبعينيات تدور أحداثه حول صراع الطبقات والعواطف، وتُعد بطولته من أبرز محطات مسيرة فاتن حمامة السينمائية.
  • E. Unterdießen
    Unterdießen is a small municipality in the district of Landsberg am Lech in Bavaria, Germany.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a616dc81908b8c1213e1d4beed completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78aef6fd08190b209a94b9ddd024c completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:51 p.m.