Triple
T21360606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuvíscar River |
E526765
|
entity |
| Predicate | hasBankInfrastructure |
P142266
|
FINISHED |
| Object | bridges in Chihuahua City |
—
|
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: bridges in Chihuahua City | Statement: [Chuvíscar River, hasBankInfrastructure, bridges in Chihuahua City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBankInfrastructure Context triple: [Chuvíscar River, hasBankInfrastructure, bridges in Chihuahua City]
-
A.
hasBanking
Indicates that one entity provides or is associated with banking services or facilities for another entity.
-
B.
hasBankOn
chosen
Indicates that one entity is located on or alongside the bank (edge) of another entity, typically a river, lake, or similar body.
-
C.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
-
D.
hasATMNetwork
Indicates that an entity operates, participates in, or is connected to a particular automated teller machine (ATM) network for financial transactions.
-
E.
hasBankType
Indicates that an entity is associated with or classified by a particular type or category of bank.
- 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8afa6afcc8190a1f5c599c11d2135 |
completed | April 22, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:08 p.m.