Triple

T4932687
Position Surface form Disambiguated ID Type / Status
Subject Richard E. Grant E110734 entity
Predicate placeOfBirth P1 FINISHED
Object Mbabane, Swaziland E95282 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: Mbabane, Swaziland | Statement: [Richard E. Grant, placeOfBirth, Mbabane, Swaziland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mbabane, Swaziland
Context triple: [Richard E. Grant, placeOfBirth, Mbabane, Swaziland]
  • A. Mbabane chosen
    Mbabane is the largest city and administrative center of Eswatini, located in the country's western highlands.
  • B. Manzini
    Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
  • C. Lobamba
    Lobamba is the traditional and legislative capital of Eswatini, serving as the seat of the Swazi monarchy and key national institutions.
  • D. Marondera
    Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
  • E. Middleveld of Eswatini
    The Middleveld of Eswatini is a central, moderately elevated and agriculturally productive region that forms the heartland of the Swazi people’s settlement and cultural life.
  • 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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd70652d988190ba4a493db510952e completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77b41c4c8190b4f714334242bc9b completed March 21, 2026, 10:49 a.m.
Created at: March 20, 2026, 1:30 p.m.