Triple
T2690597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pharr, Texas |
E58390
|
entity |
| Predicate | hasInternationalBridgeType |
P30343
|
FINISHED |
| Object | commercial truck bridge |
—
|
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: commercial truck bridge | Statement: [Pharr, Texas, hasInternationalBridgeType, commercial truck bridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInternationalBridgeType Context triple: [Pharr, Texas, hasInternationalBridgeType, commercial truck bridge]
-
A.
hasInternationalBridgeTo
Indicates a relationship where two locations are directly connected by a bridge that crosses an international border between them.
-
B.
hasBridgeTo
Indicates that one entity is connected to another by a bridge or bridging structure that allows passage or linkage between them.
-
C.
hasNumberOfBridges
Indicates the quantitative relationship specifying how many bridges are associated with a given entity.
-
D.
hasBridgeSection
Indicates that one entity includes or is associated with a specific bridge section as a distinct part or component.
-
E.
hasBridgeTypeCrossing
chosen
Indicates that a bridge is characterized by a specific type of crossing it provides or supports.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81c9b4c81908e5e0da6ac5f828b |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.