Triple

T3758821
Position Surface form Disambiguated ID Type / Status
Subject Arabia Standard Time E82112 entity
Predicate observedInCountry P3248 FINISHED
Object Beirut E4667 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: Beirut | Statement: [Arabia Standard Time, observedInCountry, Beirut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beirut
Context triple: [Arabia Standard Time, observedInCountry, Beirut]
  • A. Beirut chosen
    Beirut is the capital and largest city of Lebanon, known as a historic cultural, commercial, and financial hub of the Eastern Mediterranean.
  • B. Jounieh
    Jounieh is a coastal city in Lebanon known for its seaside resorts, vibrant nightlife, and proximity to the historic pilgrimage site of Harissa.
  • C. Tartus
    Tartus is a major Syrian port city on the Mediterranean coast that hosts Russia’s only naval facility outside the former Soviet Union.
  • D. Port of Beirut
    The Port of Beirut is Lebanon’s principal maritime gateway and commercial hub on the Mediterranean Sea, historically central to the country’s trade and economy.
  • E. Aleppo
    Aleppo is an ancient and historically significant city in northern Syria, renowned for its rich cultural heritage, medieval architecture, and role as a major trading hub along the Silk Road.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbc20b20819095fedf803aadc53a completed March 8, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e5133ba48190a18ea170e3b9e1cd completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.