Triple
T7892299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mu Ko Lanta National Park |
E183264
|
entity |
| Predicate | hasTerrestrialArea |
P79599
|
FINISHED |
| Object | minority of total area |
—
|
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: minority of total area | Statement: [Mu Ko Lanta National Park, hasTerrestrialArea, minority of total area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerrestrialArea Context triple: [Mu Ko Lanta National Park, hasTerrestrialArea, minority of total area]
-
A.
hasLandAreaRange
Indicates that an entity’s land area falls within a specified minimum-to-maximum range.
-
B.
hasLandCoverage
Indicates that a specified area or region is covered or occupied by a particular type of land surface or land use.
-
C.
territorialExtent
Indicates the geographic area or spatial range over which something extends, applies, or has jurisdiction.
-
D.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
-
E.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
- F. None of above. chosen
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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39fef2e48190a6282c217c33c57a |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92b0cd881908e715a10d3252e83 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf786ec748190b6347b0c94335550 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 5 p.m.