Triple

T12725421
Position Surface form Disambiguated ID Type / Status
Subject Michael Owusu Addo E304092 entity
Predicate birthPlace P1 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: [Michael Owusu Addo, birthPlace, Tema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tema
Context triple: [Michael Owusu Addo, birthPlace, 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. Temaʿ
    Temaʿ is a transliterated form of the biblical and historical name "Tema," associated with an oasis region and people in northwestern Arabia mentioned in ancient Near Eastern sources.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96415ebe48190ae935bc3a9b00f65 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c85c6b88190bbdd94a43915a7a4 completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:25 p.m.