Triple
T5971468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russia and Mongolia |
E132883
|
entity |
| Predicate | borderLength_km |
P57957
|
FINISHED |
| Object | 3485 |
—
|
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: 3485 | Statement: [Russia and Mongolia, borderLength_km, 3485]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderLength_km Context triple: [Russia and Mongolia, borderLength_km, 3485]
-
A.
shareLandBorderLengthApproxKm
chosen
Indicates that two entities share a land border whose length is approximately the given number of kilometers.
-
B.
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.
-
C.
hasBorderLengthWithCanada_km
Indicates the length, in kilometers, of the land or maritime border that an entity shares with Canada.
-
D.
widthKilometres
Indicates the measurement of how wide something is, expressed in kilometres.
-
E.
countryBordering
Indicates that one country shares a land or maritime boundary directly 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:03 p.m.