Triple
T27726988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ko Haa |
E697326
|
entity |
| Predicate | nearestMajorTouristHub |
P36605
|
FINISHED |
| Object | Ko Lanta |
—
|
NE NERFINISHED |
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: Ko Lanta | Statement: [Ko Haa, nearestMajorTouristHub, Ko Lanta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestMajorTouristHub Context triple: [Ko Haa, nearestMajorTouristHub, Ko Lanta]
-
A.
nearestMajorTransportHub
Indicates that one location is the closest significant transportation center (such as a major train station, airport, or bus terminal) to another location.
-
B.
nearbyHeritageStation
Indicates that one entity is located close to a heritage (historically or culturally significant) station.
-
C.
typicalNearbyLandmarks
Indicates that certain landmarks are commonly found in the vicinity of a given place or location.
-
D.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
E.
nearestEntranceStation
Indicates that one station is the closest entrance station to a given location or entity compared to all other candidate stations.
- 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_69ef590c3e288190ad54d2465af8ca4e |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 27, 2026, 3:09 p.m.