Triple
T26946489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umphang District |
E678656
|
entity |
| Predicate | nearestInternationalBorderCrossingCountry |
P165871
|
FINISHED |
| Object | Myanmar |
—
|
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: Myanmar | Statement: [Umphang District, nearestInternationalBorderCrossingCountry, Myanmar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestInternationalBorderCrossingCountry Context triple: [Umphang District, nearestInternationalBorderCrossingCountry, Myanmar]
-
A.
borderingCountryOfState
Indicates that one country shares a land or maritime boundary directly with the specified state.
-
B.
sharesInternationalBorderWith
Indicates that two geographic or political entities have a common boundary that is recognized as an international border.
-
C.
borderingCountryNearby
Indicates that one country is geographically close to, but does not necessarily share a direct land border with, another country.
-
D.
countryBordering
Indicates that one country shares a land or maritime boundary directly with another country.
-
E.
countryBorderProximity
Indicates that one country is geographically close to or directly bordering another country.
- 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65a9cb0bc8190bf8a9b319900bad5 |
completed | May 2, 2026, 8:12 p.m. |
Created at: April 27, 2026, 6:21 a.m.