Triple

T18537846
Position Surface form Disambiguated ID Type / Status
Subject Sanakhte E453012 entity
Predicate possibleSpouse P33561 FINISHED
Object Nimaathap NE NERFINISHED

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: Nimaathap | Statement: [Sanakhte, possibleSpouse, Nimaathap]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nimaathap
Context triple: [Sanakhte, possibleSpouse, Nimaathap]
  • A. Nimaathap chosen
    Nimaathap was an ancient Egyptian queen of the late 2nd Dynasty, likely a royal consort and mother of early 3rd Dynasty kings.
  • B. Nimaima
    Nimaima is a small town and municipality in the Gualivá Province of the Cundinamarca Department in central Colombia.
  • C. Nimmu
    Nimmu is a small village in the Leh district of Ladakh, India, known as a scenic stop on the Srinagar–Leh highway and a popular rafting and sightseeing point near the confluence of the Indus and Zanskar rivers.
  • D. Nimadi
    Nimadi is an Indo-Aryan language spoken primarily in the Nimar region of Madhya Pradesh in central India.
  • E. Namanve
    Namanve is an industrial and commercial area in central Uganda known for hosting the Kampala Industrial and Business Park and various manufacturing facilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d387b5548190aa030dad2cb4947e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e534030bd88190b25b95305a12a0c1 completed April 19, 2026, 7:58 p.m.
Created at: April 10, 2026, 11:37 a.m.