Triple
T29648746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moreh–Tamu crossing |
E756076
|
entity |
| Predicate | nearbyTownOnMyanmarSide |
P85286
|
FINISHED |
| Object | Tamu |
—
|
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: Tamu | Statement: [Moreh–Tamu crossing, nearbyTownOnMyanmarSide, Tamu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyTownOnMyanmarSide Context triple: [Moreh–Tamu crossing, nearbyTownOnMyanmarSide, Tamu]
-
A.
hasBorderTownOnMyanmarSide
chosen
Indicates that a town is located on the Myanmar side of a border shared with another country.
-
B.
nearCityOnMalaysianSide
Indicates that one entity is located close to a particular city that lies on the Malaysian side of a border or region.
-
C.
hasBorderStatesOnMyanmarSide
Indicates that the referenced entity consists of or includes the states that share a land border with Myanmar.
-
D.
distanceFromMawlamyine_km
Indicates the distance, measured in kilometers, between a given place or entity and Mawlamyine.
-
E.
nearCityOnSingaporeSide
Indicates that one entity is located close to a city that lies on the Singapore side of a relevant boundary or region.
- 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_69f0ef89d2c88190a6d0d5116ccd7cc9 |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69fd09840ea88190a2e6d7e577ade717 |
completed | May 7, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69fd064c49988190afadddbd04d7cb94 |
completed | May 7, 2026, 9:38 p.m. |
Created at: April 28, 2026, 6:51 p.m.