Triple
T33713154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ski municipality |
E863795
|
entity |
| Predicate | hadAreaType |
P6822
|
FINISHED |
| Object | suburban municipality |
—
|
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: suburban municipality | Statement: [Ski municipality, hadAreaType, suburban municipality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadAreaType Context triple: [Ski municipality, hadAreaType, suburban municipality]
-
A.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
B.
hasAreaNumber
Indicates that an entity is associated with a specific area identified by a numerical code.
-
C.
hasCadastralArea
Indicates that an entity possesses or is associated with a specific cadastral (official land registry) area measurement.
-
D.
typeOfAreaRepresented
Indicates that one entity specifies the kind or category of area that another entity represents.
-
E.
includesAreaType
Indicates that one entity encompasses or contains another entity of a specified area type within its scope or boundaries.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fabe07848190bd4f14ac6dfa35b6 |
completed | May 3, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:43 a.m.