Triple
T34270482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Matanza |
E879299
|
entity |
| Predicate | formsPartOfMetropolitanArea |
P294
|
FINISHED |
| Object | Greater Buenos Aires |
—
|
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: Greater Buenos Aires | Statement: [La Matanza, formsPartOfMetropolitanArea, Greater Buenos Aires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formsPartOfMetropolitanArea Context triple: [La Matanza, formsPartOfMetropolitanArea, Greater Buenos Aires]
-
A.
partOfMetropolitanArea
chosen
Indicates that one place is included within and belongs to the larger metropolitan area of another place.
-
B.
belongsToMetropolitanRegion
Indicates that one geographic or administrative area is part of, or included within, a larger metropolitan region.
-
C.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
D.
isMetropolitanArea
Indicates that a given area functions as a major urban center and its surrounding region, typically characterized by high population density and integrated economic and social activities.
-
E.
operatesInMetropolitanArea
Indicates that an entity conducts its activities or provides its services within a specified metropolitan area.
- 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_69f349b4f5fc819094b441d18e95e5f1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: May 1, 2026, 1:56 a.m.