Triple
T19609496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mfuwe |
E470690
|
entity |
| Predicate | tourismInfrastructureLevel |
P70107
|
FINISHED |
| Object | developing |
—
|
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: developing | Statement: [Mfuwe, tourismInfrastructureLevel, developing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismInfrastructureLevel Context triple: [Mfuwe, tourismInfrastructureLevel, developing]
-
A.
hasTouristInfrastructure
Indicates that a place is equipped with facilities and services designed to support and accommodate tourists.
-
B.
tourismDevelopmentLevel
chosen
Indicates the extent or intensity to which tourism-related infrastructure, services, and activities have been developed in a given area.
-
C.
infrastructureLevel
Indicates the degree or quality of infrastructure present or provided in relation to an entity or location.
-
D.
hasTourismRating
Indicates that an entity has been assigned a specific tourism-related quality or rating, reflecting its appeal or suitability for tourists.
-
E.
amenityLevel
Indicates the degree or quality of facilities, services, or conveniences provided in relation to something.
- 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640ca57a081909c05000fca52271f |
completed | April 20, 2026, 3:05 p.m. |
| PD | Predicate disambiguation | batch_69e514e166dc8190a0f147e0b4c8bbe7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.