Triple

T16081119
Position Surface form Disambiguated ID Type / Status
Subject Yanbu Governorate E390111 entity
Predicate hasCapital P204 FINISHED
Object Yanbu E91777 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: Yanbu | Statement: [Yanbu Governorate, hasCapital, Yanbu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yanbu
Context triple: [Yanbu Governorate, hasCapital, Yanbu]
  • A. Yanbu chosen
    Yanbu is a coastal city in western Saudi Arabia on the Red Sea, known as an industrial and port hub in the Medina Province.
  • B. Al Bahah
    Al Bahah is a city in southwestern Saudi Arabia known for its mild climate, forests, and mountainous landscapes that make it a popular domestic tourist destination.
  • C. 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.
  • D. Ghawwas
    Ghawwas is a notable poet associated with the Dakhni (Deccani) literary tradition of South Asia.
  • E. Al Ghaydah
    Al Ghaydah is a coastal city in eastern Yemen that serves as the administrative and commercial center of the Mahra Governorate near the border with Oman.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1844a5c68819086a13c93a787b436 completed April 17, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff798c2a48190b6eccd476a0a396f completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 4:57 a.m.