Triple
T26847464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Resistencia metropolitan area |
E675963
|
entity |
| Predicate | urbanAgglomerationAround |
P73839
|
FINISHED |
| Object | Resistencia |
—
|
NE NERFINISHED |
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: Resistencia | Statement: [Resistencia metropolitan area, urbanAgglomerationAround, Resistencia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanAgglomerationAround Context triple: [Resistencia metropolitan area, urbanAgglomerationAround, Resistencia]
-
A.
relatedUrbanArea
Indicates that one urban area is geographically or functionally associated with another urban area, such as being nearby, connected, or part of the same broader metropolitan context.
-
B.
hasUrbanAgglomeration
chosen
Indicates that an entity includes, is associated with, or is characterized by a specific urban agglomeration (a densely populated urban area and its surrounding zones).
-
C.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
cityCluster
Indicates a grouping relationship where multiple cities are associated together as part of the same cluster or urban agglomeration.
-
E.
nearestLargeUrbanArea
Indicates that one entity is the closest major city or large urban center to the other entity.
- 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_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 5:13 a.m.