Triple

T14950335
Position Surface form Disambiguated ID Type / Status
Subject Kawit E372774 entity
Predicate hasDemographicDescriptor P25372 FINISHED
Object densely populated 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: densely populated | Statement: [Kawit, hasDemographicDescriptor, densely populated]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDemographicDescriptor
Context triple: [Kawit, hasDemographicDescriptor, densely populated]
  • A. demographicsDescriptor chosen
    Indicates a descriptive attribute or classification that characterizes the demographic properties of an entity or group.
  • B. hasDemographic
    Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
  • C. hasDemographicPattern
    Indicates that there is a characteristic distribution or trend of attributes (such as age, gender, income, or ethnicity) within a population or group.
  • D. 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.
  • E. demographicsCharacteristic
    Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies 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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded68fae3c81909873b113bfcaca05 completed April 15, 2026, 12:06 a.m.
PD Predicate disambiguation batch_69de9a588c2c8190b1245a1c406f447c completed April 14, 2026, 7:49 p.m.
Created at: April 10, 2026, 2:39 a.m.