Triple

T16541522
Position Surface form Disambiguated ID Type / Status
Subject Ottoman garrisons in Syria E401829 entity
Predicate locatedIn P40 FINISHED
Object Hama E71751 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: Hama | Statement: [Ottoman garrisons in Syria, locatedIn, Hama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hama
Context triple: [Ottoman garrisons in Syria, locatedIn, Hama]
  • A. Hama chosen
    Hama is a major city in west-central Syria, historically known for its ancient waterwheels (norias) on the Orontes River and its role as an important agricultural and industrial center.
  • B. Shama
    Shama is a coastal town in Ghana known historically as a fishing community and trading post along the Gulf of Guinea.
  • C. Aokas
    Aokas is a coastal town in northern Algeria known for its Mediterranean beaches, karst caves, and location along the scenic shoreline of Béjaïa Province.
  • D. Hamey
    Hamey is a diminutive or affectionate nickname derived from the given name Hamish.
  • E. Tama
    Tama is a diminutive form of the given name Tamara, often used as a familiar or affectionate nickname.
  • 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_69d88384bc30819084229e7dcdc39a41 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3455cf4b88190b3c9e93e158a7686 completed April 18, 2026, 8:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067b0e5708190a286b8a316d6efd2 completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:15 a.m.