Triple
T25145497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Marcos Department |
E629921
|
entity |
| Predicate | borderTypeWithMexico |
P159724
|
FINISHED |
| Object | international land border |
—
|
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: international land border | Statement: [San Marcos Department, borderTypeWithMexico, international land border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderTypeWithMexico Context triple: [San Marcos Department, borderTypeWithMexico, international land border]
-
A.
borderCityOnMexicanSide
Indicates that a city is located on the Mexican side of an international border shared with another country.
-
B.
borderTypeWithVenezuela
Indicates the specific type or nature of the border that an entity shares with Venezuela.
-
C.
borderCityOnUSSide
Indicates that a city is located on the U.S. side of an international border shared with another country.
-
D.
bordersMexicanState
Indicates that one entity shares a land or maritime boundary with a state of Mexico.
-
E.
borderWithUnitedStatesVia
Indicates that one entity shares a border with the United States specifically through or along the second entity (such as a body of water, territory, or region).
- 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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f5f7a205688190b8f36bff5013247c |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 18, 2026, 6:30 a.m.