Triple
T6731514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas |
E153644
|
entity |
| Predicate | borderLengthWithMexico_km |
P57957
|
FINISHED |
| Object | 2033 |
—
|
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: 2033 | Statement: [Texas, borderLengthWithMexico_km, 2033]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderLengthWithMexico_km Context triple: [Texas, borderLengthWithMexico_km, 2033]
-
A.
hasBorderLengthWithCanada_km
Indicates the length, in kilometers, of the land or maritime border that an entity shares with Canada.
-
B.
hasBorderLengthWithUSA
Indicates that the length of the land or maritime border shared between a given country or region and the USA has a specified measurement.
-
C.
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.
-
D.
distanceToMexicoBorder
Indicates the measured or estimated distance between a given location or entity and the border of Mexico.
-
E.
shareLandBorderLengthApproxKm
chosen
Indicates that two entities share a land border whose length is approximately the given number of kilometers.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:09 p.m.