Triple
T35492491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinto metropolitan area |
E1025766
|
entity |
| Predicate | hasFunctionalRelation |
P149304
|
FINISHED |
| Object | commuter belt of Pinto |
—
|
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: commuter belt of Pinto | Statement: [Pinto metropolitan area, hasFunctionalRelation, commuter belt of Pinto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFunctionalRelation Context triple: [Pinto metropolitan area, hasFunctionalRelation, commuter belt of Pinto]
-
A.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
B.
functionallyRelatedTo
chosen
Indicates that two entities are connected through a functional relationship, where the operation, behavior, or role of one depends on, influences, or complements that of the other.
-
C.
hasShapeRelation
Indicates that one entity is related to another through a specific geometric or spatial shape relationship (such as similarity, congruence, or containment of shape).
-
D.
hasSubordinateFunction
Indicates that one function operates under the authority, control, or scope of another function as its subordinate.
-
E.
hasCorrelationFunctions
Indicates that there exist correlation functions characterizing statistical or relational dependencies between the associated entities.
- 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_69f76dfbcdd881908c7b0b6bc502252b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:04 p.m.