Triple

T11880403
Position Surface form Disambiguated ID Type / Status
Subject Apamea on the Orontes E282642 entity
Predicate near P350 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: [Apamea on the Orontes, near, Hama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hama
Context triple: [Apamea on the Orontes, near, 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8be1cad5c8190a45dfb0f0cc2a512 completed April 10, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f281e6f8888190bc8495b1261a86df completed April 29, 2026, 10:10 p.m.
Created at: April 8, 2026, 9:44 p.m.