Triple

T14560672
Position Surface form Disambiguated ID Type / Status
Subject Amasia E341655 entity
Predicate ancientNameForm P20952 FINISHED
Object Amaseia E325073 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: Amaseia | Statement: [Amasia, ancientNameForm, Amaseia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amaseia
Context triple: [Amasia, ancientNameForm, Amaseia]
  • A. Amaseia chosen
    Amaseia was an ancient city in northern Anatolia that served as the early capital of the Kingdom of Pontus and an important regional political and cultural center.
  • B. Ambracia
    Ambracia was an ancient Greek city in Epirus that became an important regional center and later the capital of King Pyrrhus.
  • C. Taurisium
    Taurisium is an ancient fortified settlement in present-day North Macedonia, traditionally regarded as the birthplace of the Byzantine emperor Justinian I.
  • D. Argiletum
    Argiletum was an ancient street in Rome that connected the Roman Forum to the Subura district and later became partly occupied by the Forum of Nerva.
  • E. Amaliapoli
    Amaliapoli is a small coastal town in central Greece known for its scenic beaches and tranquil setting on the Pagasetic Gulf.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb389d0f48190a1d9d69456d1cbe1 completed April 14, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ac294748190a4bfeed8c5fd9e94 completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:23 a.m.