Triple

T8024155
Position Surface form Disambiguated ID Type / Status
Subject Qardaha E186810 entity
Predicate nearbyCity P350 FINISHED
Object Latakia E62578 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: Latakia | Statement: [Qardaha, nearbyCity, Latakia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Latakia
Context triple: [Qardaha, nearbyCity, Latakia]
  • A. Latakia chosen
    Latakia is a major port city on Syria's Mediterranean coast and an important economic and cultural center for the country.
  • 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. Homs
    Homs is one of Syria’s largest and oldest cities, historically a major commercial and industrial center located in the western part of the country.
  • E. Raqqa
    Raqqa is a city in northern Syria that became widely known as the de facto capital of the Islamic State (ISIS) during its control from 2014 to 2017.
  • 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_69ca82ad4e2c8190a693e3c9e30fe66f completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3e90c7348190abc1013a312e4f1a completed March 31, 2026, 3:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc93b18a6c81908a3a4bc25552d97b completed April 1, 2026, 3:40 a.m.
Created at: March 30, 2026, 5:21 p.m.