Triple

T494208
Position Surface form Disambiguated ID Type / Status
Subject Lebanon Conference (1944) E10254 entity
Predicate location P40 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: [Lebanon Conference (1944), location, Beirut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beirut
Context triple: [Lebanon Conference (1944), location, 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. Tartus
    Tartus is a major Syrian port city on the Mediterranean coast that hosts Russia’s only naval facility outside the former Soviet Union.
  • C. 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.
  • D. Haifa
    Haifa is a major Israeli city on the Mediterranean coast, known for its significant port, mixed Jewish-Arab population, and the terraced Baháʼí Gardens on Mount Carmel.
  • E. Tunis
    Tunis is the capital and largest city of Tunisia, serving as a major political, economic, and cultural center in the Arab world.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f0fbfa408190aeb3b93996a35c00 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4984b8c848190a35d98d6d5858304 completed March 1, 2026, 7:49 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.