Triple

T10601955
Position Surface form Disambiguated ID Type / Status
Subject Al-Ahsa E275768 entity
Predicate hasCity P316 FINISHED
Object Mubarraz E779421 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: Mubarraz | Statement: [Al-Ahsa, hasCity, Mubarraz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mubarraz
Context triple: [Al-Ahsa, hasCity, Mubarraz]
  • A. Al-Mubarraz chosen
    Al-Mubarraz is a major city in Saudi Arabia’s Eastern Province, forming a twin urban area with nearby Hofuf in the fertile Al-Ahsa oasis region.
  • B. El Mounib
    El Mounib is a district in Giza, Egypt, known for serving as a major southern transport hub on the Cairo Metro network.
  • C. Shuja
    Shuja is a given name most notably associated with Shuja Shah Durrani, a 19th-century ruler of the Durrani Empire in Afghanistan.
  • D. Mawlaik
    Mawlaik is a town in northwestern Myanmar’s Sagaing Region, situated along the Chindwin River and serving as a local administrative and trading center.
  • E. Al-Mohager
    Al-Mohager is a 1994 Egyptian historical drama film by director Youssef Chahine that offers a modern, allegorical retelling of the biblical story of Joseph.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6ded61d5c8190b13890c964b59949 completed April 8, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95ea8f1688190aa36e29b52667d26 completed April 10, 2026, 8:33 p.m.
Created at: April 8, 2026, 7:31 p.m.