Triple

T1498720
Position Surface form Disambiguated ID Type / Status
Subject Xikou, Fenghua, Zhejiang, Qing Empire E29745 entity
Predicate historicalPopulationScale P17235 FINISHED
Object small town 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: small town | Statement: [Xikou, Fenghua, Zhejiang, Qing Empire, historicalPopulationScale, small town]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: historicalPopulationScale
Context triple: [Xikou, Fenghua, Zhejiang, Qing Empire, historicalPopulationScale, small town]
  • A. hasPopulationScale chosen
    Indicates the relative size or magnitude of a population associated with an entity, typically expressed as a qualitative or categorical scale.
  • B. historicalPopulationMovement
    Indicates the movement or migration of a population from one place to another during a specific historical period or event.
  • C. formerPopulation
    Indicates that an entity once had a certain population value or size during a past time period but no longer does.
  • D. hasPopulationAsOf
    Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
  • E. religiousCompositionHistorical
    Indicates the historical distribution or makeup of religious affiliations within a population or group over time.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6f0ce988190aafab4a6e0dfd710 completed March 1, 2026, 11:08 p.m.
PD Predicate disambiguation batch_69a4c48a8cf48190a6ebf8d44a608a06 completed March 1, 2026, 10:58 p.m.
Created at: March 1, 2026, 8:12 p.m.