Triple
T11258787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr Ruth Segomotsi Mompati District |
E266507
|
entity |
| Predicate | hasMunicipalCodePrefix |
P3943
|
FINISHED |
| Object | NW |
—
|
LITERAL 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: NW | Statement: [Dr Ruth Segomotsi Mompati District, hasMunicipalCodePrefix, NW]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalCodePrefix Context triple: [Dr Ruth Segomotsi Mompati District, hasMunicipalCodePrefix, NW]
-
A.
hasMunicipalityCode
chosen
Indicates that an entity is associated with a specific official municipality code used for administrative or identification purposes.
-
B.
hasStationCodePrefix
Indicates that one entity’s station code begins with the prefix specified by the other entity.
-
C.
hasMunicipalDistrictNumber
Indicates that a municipality or local administrative unit is assigned a specific district number within its municipal structure.
-
D.
hasPostalCodePrefix
Indicates that a location’s postal code begins with a specified sequence of characters.
-
E.
hasAirportCodePrefix
Indicates that an airport’s code begins with a specified sequence of characters.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e936cb048190b4d6fb2851ef8932 |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d78793c00481908a3f764b610b77a4 |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.