Triple

T18758443
Position Surface form Disambiguated ID Type / Status
Subject Samosata E458708 entity
Predicate alternativeName P39 FINISHED
Object Samsat NE NERFINISHED

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: Samsat | Statement: [Samosata, alternativeName, Samsat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samsat
Context triple: [Samosata, alternativeName, Samsat]
  • A. Samsat chosen
    Samsat is a small town and district in Turkey’s Adıyaman Province, located on the Euphrates River near the massive Atatürk Dam.
  • B. Salik
    Salik is Dubai’s electronic toll collection system used on major roads and bridges to manage traffic and generate road-use revenue.
  • C. Setia
    Setia is the ancient Latin town that later became known as Sezze, located in the Lazio region of central Italy.
  • D. Sitra
    Sitra is a small island in Bahrain known for its residential communities, industrial facilities, and role in the country’s oil and gas infrastructure.
  • E. Citura
    Citura is the public transport operator responsible for managing Reims’ urban transit network, including its tramway system, in northeastern France.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d395dba0819087568404508590cb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e579f42d0881909bd9ca9c7916516a completed April 20, 2026, 12:57 a.m.
Created at: April 10, 2026, 11:52 a.m.