Triple
T32506021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | eMadlangeni Local Municipality |
E830794
|
entity |
| Predicate | hasPotentialSector |
P116570
|
FINISHED |
| Object | eco-tourism |
—
|
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: eco-tourism | Statement: [eMadlangeni Local Municipality, hasPotentialSector, eco-tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPotentialSector Context triple: [eMadlangeni Local Municipality, hasPotentialSector, eco-tourism]
-
A.
hasPotential
Indicates that an entity possesses the capacity or possibility to develop, achieve, or exhibit a particular state, quality, or outcome in the future.
-
B.
hasMarketSector
chosen
Indicates that an entity operates within, is associated with, or belongs to a particular market sector or industry segment.
-
C.
hasResourcePotential
Indicates that an entity possesses the capacity or suitability to provide, generate, or support a particular resource in the future.
-
D.
hasConnectionPotential
Indicates that there exists a possibility or capacity for a meaningful connection or relationship to form between the entities.
-
E.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
- 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_69f349219cb8819087e120f509629c1b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
Created at: May 1, 2026, 1 a.m.