Triple
T36282132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zona Norte, Tijuana |
E892966
|
entity |
| Predicate | borderCrossingInfluence |
P201156
|
FINISHED |
| Object | U.S. dollar widely accepted |
—
|
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: U.S. dollar widely accepted | Statement: [Zona Norte, Tijuana, borderCrossingInfluence, U.S. dollar widely accepted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderCrossingInfluence Context triple: [Zona Norte, Tijuana, borderCrossingInfluence, U.S. dollar widely accepted]
-
A.
borderCrossingArea
Indicates an area specifically designated for crossing a border between two jurisdictions or territories.
-
B.
borderCrossingDistribution
Indicates the pattern or allocation of border crossings across locations, times, or groups.
-
C.
borderCrossingStatus
Indicates the current state or outcome of an entity’s attempt to cross a border (e.g., allowed, denied, pending, or completed).
-
D.
borderCrossingDirectionTo
Indicates the direction in which a border crossing occurs from one side or territory to another.
-
E.
borderCrossingRouteTo
Indicates a route or path used to travel across a border from one place or jurisdiction to another.
- 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_69f76e4955c08190b8cfddca34fc0242 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffcc6182b48190afb598ced6500e66 |
completed | May 10, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69ffcbb363748190bc6f8d038fba44ff |
completed | May 10, 2026, 12:05 a.m. |
| PDg | Predicate description generation | batch_69ffcc60dae48190b76b3eb7e2ce5103 |
completed | May 10, 2026, 12:08 a.m. |
Created at: May 3, 2026, 4:09 p.m.