Triple

T8774162
Position Surface form Disambiguated ID Type / Status
Subject Fort St. Anthony E208535 entity
Predicate locatedIn P40 FINISHED
Object Axim E577141 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: Axim | Statement: [Fort St. Anthony, locatedIn, Axim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Axim
Context triple: [Fort St. Anthony, locatedIn, Axim]
  • A. Axim chosen
    Axim is a coastal town in southwestern Ghana known for its historic forts, fishing industry, and beaches along the Atlantic Ocean.
  • B. Axius
    Axius is the ancient name of the Orontes River, a historically significant waterway in the Near East that flows through modern-day Lebanon, Syria, and Turkey.
  • C. Akeanon
    Akeanon is a Central Philippine language variety spoken by the Aklanon people of Aklan province in the Philippines, noted for its distinctive phonology and vocabulary.
  • D. Telesia
    Telesia was an important ancient town in the region of Samnium in south-central Italy, known for its strategic and military significance in pre-Roman and Roman times.
  • E. Xanéu
    Xanéu is an alternative name for the Terena language, an Arawakan language spoken by the Terena people of Brazil.
  • 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_69ca835edb4481909b4aafb616dc5eb7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f2ef3288190988bd69e8a02e741 completed March 31, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51c760b48190b2138cd2861b2c61 completed April 3, 2026, 5:36 a.m.
Created at: March 30, 2026, 6:41 p.m.