Triple
T27191014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myanmar immigration checkpoint at Htee Khee |
E683474
|
entity |
| Predicate | neighboringCountrySide |
P68114
|
FINISHED |
| Object | Thailand |
—
|
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: Thailand | Statement: [Myanmar immigration checkpoint at Htee Khee, neighboringCountrySide, Thailand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neighboringCountrySide Context triple: [Myanmar immigration checkpoint at Htee Khee, neighboringCountrySide, Thailand]
-
A.
borderCountrySide
Indicates that one country shares a land border with the side or region of another country.
-
B.
borderingCountryOnOtherSide
Indicates that one country lies on the opposite side of a shared border relative to another country.
-
C.
borderingCountryNearby
Indicates that one country is geographically close to, but does not necessarily share a direct land border with, another country.
-
D.
geographicallyAdjacentTo
chosen
Indicates that two geographic entities share a common boundary or are directly next to each other in space.
-
E.
countryBorderDirection
Indicates the cardinal or relative direction in which one country lies in relation to the border it shares with another country.
- 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_69eefad140408190b8586fdebcf9af46 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 27, 2026, 9:32 a.m.