Triple
T28393891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saulsville |
E719230
|
entity |
| Predicate | linkedGeographicallyTo |
P146651
|
FINISHED |
| Object | Atteridgeville |
E192103
|
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: Atteridgeville | Statement: [Saulsville, linkedGeographicallyTo, Atteridgeville]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedGeographicallyTo Context triple: [Saulsville, linkedGeographicallyTo, Atteridgeville]
-
A.
hasGeographicConnectionTo
chosen
Indicates a relationship where two entities are linked through a shared or relevant geographic feature, location, or spatial association.
-
B.
linkedLocation
Indicates that one location is associated or connected to another location in a meaningful way, such as being related, referenced, or contextually tied.
-
C.
commonlyLinkedTo
Indicates that one entity is frequently or typically associated, connected, or co-occurring with another entity.
-
D.
associatedThrough
Indicates that two entities are connected or related to each other by means of a specified intermediary, context, or linkage.
-
E.
relatedMap
Indicates that one entity is associated with another through a mapping or correspondence relationship, typically linking related items or concepts.
- F. None of above.
Provenance (4 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_69eff6efd1b08190ae3cefd4f11388a2 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1ccf2185d48190bf9fbd39164bf278 |
completed | June 1, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 28, 2026, 1:15 a.m.