Triple

T2489131
Position Surface form Disambiguated ID Type / Status
Subject Horahane Roma E51997 entity
Predicate oftenIdentifyWith P3100 FINISHED
Object local Muslim majority populations 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: local Muslim majority populations | Statement: [Horahane Roma, oftenIdentifyWith, local Muslim majority populations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: oftenIdentifyWith
Context triple: [Horahane Roma, oftenIdentifyWith, local Muslim majority populations]
  • A. recognizedAlongside
    Indicates that two or more entities are acknowledged, identified, or honored together in the same context or occasion.
  • B. oftenConfusedWith
    Indicates that one entity is frequently mistaken for or thought to be another due to similarity or ambiguity.
  • C. oftenAccompaniedBy chosen
    Indicates that one entity is frequently found together with, occurs alongside, or is commonly associated in presence or use with another entity.
  • D. oftenInvolvedWith
    Indicates that one entity frequently participates in or is commonly associated with activities, events, or situations involving another entity.
  • E. associatedWithSee
    Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
  • 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_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd20b6d008190acec0eb172e218c9 completed March 7, 2026, 7:21 a.m.
PD Predicate disambiguation batch_69abd0b7cf088190bcff4dac6150044c completed March 7, 2026, 7:16 a.m.
Created at: March 6, 2026, 9:45 p.m.