Triple

T13851120
Position Surface form Disambiguated ID Type / Status
Subject Shuozhou E332942 entity
Predicate hasAdministrativeDivision P747 FINISHED
Object Shuocheng District E1113110 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: Shuocheng District | Statement: [Shuozhou, hasAdministrativeDivision, Shuocheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shuocheng District
Context triple: [Shuozhou, hasAdministrativeDivision, Shuocheng District]
  • A. Shuocheng District chosen
    Shuocheng District is the central urban district and administrative heart of Shuozhou City in Shanxi Province, China.
  • B. Yicheng District
    Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
  • C. Lucheng District
    Lucheng District is the central urban district and administrative, commercial, and cultural core of Wenzhou in Zhejiang Province, China.
  • D. Hecheng District
    Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
  • E. Chengzhong District
    Chengzhong District is a central urban district of Xining, the capital city of Qinghai Province in northwest China.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02d8fb788190baef7537be2baecb completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fdf06a3e208190a24e6cd9cb97e99c completed May 8, 2026, 2:17 p.m.
Created at: April 9, 2026, 10:14 p.m.