Triple

T3723678
Position Surface form Disambiguated ID Type / Status
Subject Ayyubid dynasty E81697 entity
Predicate notableCity P2813 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: [Ayyubid dynasty, notableCity, Hama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hama
Context triple: [Ayyubid dynasty, notableCity, 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. Hamey
    Hamey is a diminutive or affectionate nickname derived from the given name Hamish.
  • C. Tama
    Tama is a region in western Tokyo, Japan, encompassing several suburban cities and towns that serve as residential and commercial areas for the greater Tokyo metropolis.
  • D. Tama
    Tama was a Japanese light cruiser of the Imperial Japanese Navy that served in World War II before being sunk during the Battle off Cape Engaño in 1944.
  • E. Hase
    The Hase is a river in northwestern Germany that flows through Lower Saxony and North Rhine-Westphalia, passing towns such as Quakenbrück before joining the Ems.
  • 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_69ad8b1b7ef081908d2d381bbf54985a completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcaf3f2ec8190a3a8f363cfb762f3 completed March 8, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4ce1b25088190958c427c932641e1 completed March 14, 2026, 2:55 a.m.
Created at: March 8, 2026, 3:34 p.m.