Triple

T1222289
Position Surface form Disambiguated ID Type / Status
Subject Alquízar E26248 entity
Predicate demographicsType P343 FINISHED
Object municipal population 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: municipal population | Statement: [Alquízar, demographicsType, municipal population]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: demographicsType
Context triple: [Alquízar, demographicsType, municipal population]
  • A. demographics chosen
    Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
  • B. demographicsLabel
    Indicates the categorical demographic group or segment that an entity is associated with or classified under.
  • C. demographicsCharacteristic
    Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
  • D. demographicsNote
    Indicates that there is an associated note or commentary describing demographic-related information about an entity.
  • E. demographicCharacteristic
    Indicates that one entity specifies or describes a demographic attribute or feature (such as age, gender, ethnicity, or similar population-related trait) of another entity.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be21a2bc819094b47580d7c5cdf8 completed March 1, 2026, 10:30 p.m.
PD Predicate disambiguation batch_69a4bb644af08190ba25905f20adb01a completed March 1, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:47 p.m.