Triple
T25525783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Buccaneers |
E639771
|
entity |
| Predicate | associatedWithTownship |
P22464
|
FINISHED |
| Object | Soweto |
—
|
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: Soweto | Statement: [The Buccaneers, associatedWithTownship, Soweto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithTownship Context triple: [The Buccaneers, associatedWithTownship, Soweto]
-
A.
relationshipToTownship
Indicates the specific type of relationship or association that an entity has with a particular township.
-
B.
associatedWithCounty
Indicates that an entity has a relationship or linkage to a specific county, such as jurisdiction, location, or administrative association.
-
C.
associatedWithCountySeat
Indicates that an entity has a relationship or connection to a county’s administrative center or county seat.
-
D.
hasTownship
chosen
Indicates that one administrative area or jurisdiction includes or is associated with a specific township.
-
E.
associatedWithSubdivision
Indicates that one entity has a connection or linkage to a specific administrative or organizational subdivision.
- F. None of above.
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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: April 21, 2026, 3:10 p.m.