Triple

T12823229
Position Surface form Disambiguated ID Type / Status
Subject Doha Corniche E306583 entity
Predicate hasView P854 FINISHED
Object Doha Bay E306582 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: Doha Bay | Statement: [Doha Corniche, hasView, Doha Bay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doha Bay
Context triple: [Doha Corniche, hasView, Doha Bay]
  • A. Doha Bay chosen
    Doha Bay is a prominent natural harbor along the coast of Doha, Qatar, known for its waterfront skyline and cultural landmarks.
  • B. بقيق
    بقيق هي مدينة سعودية في المنطقة الشرقية تشتهر بكونها مركزاً مهماً لصناعة النفط ومعالجة البترول.
  • C. Ras Al Khair
    Ras Al Khair is an industrial city on Saudi Arabia’s eastern coast, known for its major mining, minerals processing, and maritime industries.
  • D. Nad Al Sheba
    Nad Al Sheba is a district in Dubai, United Arab Emirates, best known for its major horse racing facilities and upscale residential developments.
  • E. Kuwait Bay
    Kuwait Bay is a shallow, semi-enclosed inlet of the Persian Gulf along the coast of Kuwait, known for its ecological importance and its role in the country’s maritime and urban 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e9fcc8c8190a926ab0481d28f14 completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af4f56108190b75dbf9bb144e94a completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:32 p.m.