Triple

T2334314
Position Surface form Disambiguated ID Type / Status
Subject Najd E44274 entity
Predicate borders P224 FINISHED
Object Asir E40054 NE 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: Asir | Statement: [Najd, borders, Asir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asir
Context triple: [Najd, borders, Asir]
  • A. Asir region chosen
    The Asir region is a mountainous, relatively lush and temperate area in southwestern Saudi Arabia known for its terraced agriculture, distinctive architecture, and cultural heritage.
  • B. Al Uwayqilah
    Al Uwayqilah is a small town located in the Northern Borders Region of Saudi Arabia, near the country’s frontier with Iraq.
  • C. Al-Awja
    Al-Awja is a small village near Tikrit in northern Iraq, best known as the birthplace and burial site of former Iraqi president Saddam Hussein.
  • D. Nasiriyah
    Nasiriyah is a significant city in southern Iraq known as a regional administrative center and a hub near several important archaeological sites such as the ancient city of Ur.
  • E. Sauda
    Sauda is a small industrial town and municipality in Rogaland county, Norway, known for its hydropower-based industry and dramatic fjord and mountain landscape.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a889132b488190bbb43ad4780ddd92 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc685f05481909c863b29d1f6bacd completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae8979bca08190aac46ef3dc1a2be2 completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:51 p.m.