Triple

T7879207
Position Surface form Disambiguated ID Type / Status
Subject Tema Industrial Area E182934 entity
Predicate locatedIn P40 FINISHED
Object Tema E182923 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: Tema | Statement: [Tema Industrial Area, locatedIn, Tema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tema
Context triple: [Tema Industrial Area, locatedIn, Tema]
  • A. Tema chosen
    Tema is a major port and industrial city on the Atlantic coast of Ghana, located east of the capital Accra.
  • B. Tema
    Tema is a biblical figure mentioned in the Old Testament, traditionally regarded as a descendant of Ishmael and associated with a region or tribe in northwestern Arabia.
  • C. Tema
    Tema is a city located within Egypt's Sohag Governorate, known as a regional center in Upper Egypt.
  • D. Tema Mantse
    Tema Mantse is the traditional Ga chief and custodian of customary authority for the coastal city of Tema in Ghana.
  • E. Tematantongo
    Tematantongo is a settlement located on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
  • 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_69ca828a17248190b46defe758bc5ad3 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb39be7ab88190affcd353a0cd37fa completed March 31, 2026, 3:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccec5f00b48190b35f7cab67e7e5f9 completed April 1, 2026, 9:58 a.m.
Created at: March 30, 2026, 4:57 p.m.