Triple

T7103964
Position Surface form Disambiguated ID Type / Status
Subject Catholic community of Nagasaki E165527 entity
Predicate estimatedCharacteristic P56672 FINISHED
Object one of the largest Catholic concentrations in Japan 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: one of the largest Catholic concentrations in Japan | Statement: [Catholic community of Nagasaki, estimatedCharacteristic, one of the largest Catholic concentrations in Japan]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: estimatedCharacteristic
Context triple: [Catholic community of Nagasaki, estimatedCharacteristic, one of the largest Catholic concentrations in Japan]
  • A. dataCharacteristic
    Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
  • B. describesCharacteristicOf chosen
    Indicates that one entity expresses or specifies a characteristic, feature, or property of another entity.
  • C. eraCharacteristic
    Indicates that a particular quality, feature, or attribute is characteristic of, or typically associated with, a given historical or temporal era.
  • D. catalogCharacteristic
    Indicates that a catalog has a specific characteristic or attribute associated with it.
  • E. trainingCharacteristic
    Indicates that an entity has a specific property, feature, or quality related to training (such as method, intensity, or style).
  • 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_69c6887fcddc8190a5d58908f6dee590 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e58b3f708190bebca7d4c4db40f2 completed March 27, 2026, 8:16 p.m.
PD Predicate disambiguation batch_69c6e1c313e481908b61a23fc89f9332 completed March 27, 2026, 8 p.m.
Created at: March 27, 2026, 2:42 p.m.