Triple
T26493613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tak province |
E669221
|
entity |
| Predicate | borderTypeWithMyanmar |
P182381
|
FINISHED |
| Object | land border |
—
|
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: land border | Statement: [Tak province, borderTypeWithMyanmar, land border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderTypeWithMyanmar Context triple: [Tak province, borderTypeWithMyanmar, land border]
-
A.
borderTypeWithNepal
Indicates the specific nature or classification of the border relationship that an entity shares with Nepal.
-
B.
borderTypeWithMongolia
Indicates the specific nature or classification of the border that an entity shares with Mongolia.
-
C.
hasBorderTownOnMyanmarSide
Indicates that a town is located on the Myanmar side of a border shared with another country.
-
D.
borderTypeWithVietnam
Indicates the type or nature of the border relationship that an entity shares with Vietnam.
-
E.
borderTypeWithIndonesia
Indicates the type or nature of the border that an entity shares with Indonesia.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f78d7211a48190bfb59c406f0bf12f |
completed | May 3, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c6014e08190864785a4fe3e8e73 |
completed | May 3, 2026, 5:56 p.m. |
Created at: April 27, 2026, 1:06 a.m.