Triple

T1917355
Position Surface form Disambiguated ID Type / Status
Subject Jingzhou E40047 entity
Predicate hasCityWallFeature P22477 FINISHED
Object moat LITERAL 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: moat | Statement: [Jingzhou, hasCityWallFeature, moat]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCityWallFeature
Context triple: [Jingzhou, hasCityWallFeature, moat]
  • A. hasPeaceWalls
    Indicates that there exist physical barriers or walls separating groups or areas to reduce or prevent conflict or violence between them.
  • B. hasHistoricTownWallsRemnants
    Indicates that remnants of historic town walls are present and associated with the subject entity.
  • C. isFortifiedCity
    Indicates that a city is strengthened with defensive structures or fortifications, such as walls, ramparts, or similar protective works.
  • D. hasFortifications chosen
    Indicates that one entity possesses or is equipped with defensive structures or fortification works associated with it.
  • E. containsFortress
    Indicates that a location or area includes a fortress within its boundaries.
  • F. None of above.

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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb2107fe48190bafff825f1f805ad completed March 7, 2026, 5:05 a.m.
PD Predicate disambiguation batch_69abafed2ab481908920334e77b1021b completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:35 p.m.