Triple
T4551500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portugal and Spain |
E110173
|
entity |
| Predicate | shareLandBorderLengthApproxKm |
P57957
|
FINISHED |
| Object | 1200 |
—
|
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: 1200 | Statement: [Portugal and Spain, shareLandBorderLengthApproxKm, 1200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareLandBorderLengthApproxKm Context triple: [Portugal and Spain, shareLandBorderLengthApproxKm, 1200]
-
A.
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.
-
B.
countryBordering
Indicates that one country shares a land or maritime boundary directly with another country.
-
C.
continentBorders
Indicates that one continent shares a land or maritime boundary directly with another continent.
-
D.
shareLandBorderRegion
Indicates that two regions are adjacent such that their land areas directly touch along a common boundary.
-
E.
hasBorderLengthWithCanada_km
Indicates the length, in kilometers, of the land or maritime border that an entity shares with Canada.
- 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f7b9748190af29d02fc77b02e0 |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:05 p.m.