Triple
T19479690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard E. Grant |
E487346
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Mbabane, Swaziland |
—
|
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: 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.
Siphofaneni, Eswatini
Siphofaneni is a rural town in central Eswatini known as an agricultural and transport hub situated near the Great Usutu River.
-
B.
Mbabane
chosen
Mbabane is the largest city and administrative center of Eswatini, located in the country's western highlands.
-
C.
Manzini
Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
-
D.
Big Bend, Eswatini
Big Bend, Eswatini is a small town in southeastern Eswatini known primarily for its sugar plantations and agro-industrial activities.
-
E.
Lobamba
Lobamba is the traditional and legislative capital of Eswatini, serving as the seat of the Swazi monarchy and key national institutions.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6343882a88190b3cfa65e6cac80d3 |
completed | April 20, 2026, 2:12 p.m. |
Created at: April 10, 2026, 1:39 p.m.