Triple

T18453095
Position Surface form Disambiguated ID Type / Status
Subject Damascus Eyalet E450835 entity
Predicate contains P35 FINISHED
Object Baniyas 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: Baniyas | Statement: [Damascus Eyalet, contains, Baniyas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baniyas
Context triple: [Damascus Eyalet, contains, Baniyas]
  • A. Baniyas chosen
    Baniyas is a coastal city in northwestern Syria on the Mediterranean Sea, known for its port, oil refinery, and proximity to other Latakia Governorate towns.
  • B. Baniyas
    Baniyas is a professional football club based in the Baniyas area of Abu Dhabi in the United Arab Emirates, known for competing in the UAE Pro League.
  • C. Bani
    Bani was a daughter of the prominent Indian freedom fighter and lawyer Chittaranjan (C. R.) Das.
  • D. Bani
    Bani is a coastal municipality in the province of Pangasinan in the Philippines, known for its beaches, agricultural produce, and scenic rural landscapes.
  • E. Bakhdida
    Bakhdida is a historically Assyrian Christian town in northern Iraq, known for its ancient churches and location in the Nineveh Plains near Mosul.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5264a49ec8190aa43381d93a55e91 completed April 19, 2026, 7 p.m.
Created at: April 10, 2026, 11:31 a.m.