Triple
T22628329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laos border |
E558482
|
entity |
| Predicate | landBorderLengthWithChina_km |
P57957
|
FINISHED |
| Object | about 475 |
—
|
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: about 475 | Statement: [Laos border, landBorderLengthWithChina_km, about 475]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landBorderLengthWithChina_km Context triple: [Laos border, landBorderLengthWithChina_km, about 475]
-
A.
hasInternationalBoundaryLengthWithChina
Indicates that there exists a shared land or river border between the subject entity and China, and specifies the length of that international boundary.
-
B.
shareLandBorderLengthApproxKm
chosen
Indicates that two entities share a land border whose length is approximately the given number of kilometers.
-
C.
borderTypeWithChina
Indicates the type or nature of the border relationship an entity has with China.
-
D.
longestLandBorderWith
Indicates that two entities share a land border and that this border is the longest land border for at least one of the entities.
-
E.
maritimeBoundaryLengthApproxKm
Indicates the approximate length, measured in kilometers, of a state's maritime boundary or coastline.
- 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f16e3ed1d48190a093013d829901b9 |
completed | April 29, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69ee62855558819080da946c7b35a160 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 3:02 p.m.