Triple

T11884949
Position Surface form Disambiguated ID Type / Status
Subject Schongau E282754 entity
Predicate locatedNear P294 FINISHED
Object Peiting E795428 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: Peiting | Statement: [Schongau, locatedNear, Peiting]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peiting
Context triple: [Schongau, locatedNear, Peiting]
  • A. Peiting chosen
    Peiting is a Bavarian municipality in southern Germany known for its location in the Alpine foothills and its historic market-town character.
  • B. Liyang
    Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
  • C. Licheng
    Licheng is the courtesy name of the Daoguang Emperor, a Qing dynasty ruler of China in the early 19th century.
  • D. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • E. Putian
    Putian is a coastal prefecture-level city in southeastern China known for its manufacturing industries, especially footwear, and its historical and cultural heritage within Fujian province.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d3a02ad4819090faef0e0be732ee completed April 10, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6389ba08190b07fac8e90da0f5b completed May 2, 2026, 1:03 p.m.
Created at: April 8, 2026, 9:44 p.m.