Triple
T26525638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mae Hong Son Airport |
E670679
|
entity |
| Predicate | connectsRemoteProvince |
P181028
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mae Hong Son Airport, connectsRemoteProvince, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsRemoteProvince Context triple: [Mae Hong Son Airport, connectsRemoteProvince, true]
-
A.
connectsProvinceOrRegion
Indicates that one entity serves to link or provide a connection between a specific province or region and another entity.
-
B.
connectsProvincesAlong
Indicates a relationship where something serves as a link or route joining multiple provinces along a specified path or alignment.
-
C.
connectsRegionalCity
Indicates a relationship where one entity serves as a link or transport route between a regional city and another location.
-
D.
connectsStates
Indicates a relationship where one entity serves as a link or route that joins two or more states together.
-
E.
connectsCountryOrRegion
Indicates that one entity establishes a connection, link, or association to a specific country or region.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
| PDg | Predicate description generation | batch_69f760a2a90c8190b8fbc55412ab752b |
completed | May 3, 2026, 2:50 p.m. |
Created at: April 27, 2026, 1:31 a.m.