Triple
T155982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magdalena Contreras |
E3182
|
entity |
| Predicate | hasMunicipalSeat |
P1474
|
FINISHED |
| Object | Barrio de La Magdalena |
—
|
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: Barrio de La Magdalena | Statement: [Magdalena Contreras, hasMunicipalSeat, Barrio de La Magdalena]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalSeat Context triple: [Magdalena Contreras, hasMunicipalSeat, Barrio de La Magdalena]
-
A.
hasMunicipalGovernment
Indicates that an entity is administered or governed by a municipal-level governmental authority.
-
B.
hasAdministrativeCenter
chosen
Indicates that an administrative unit (such as a region, district, or municipality) has a specific place designated as its main governing or administrative center.
-
C.
countySeat
Indicates that one place serves as the administrative center or capital of a county.
-
D.
isProvincialCapital
Indicates that a location serves as the administrative capital of a province within a country or region.
-
E.
hasPopulationCenter
Indicates that an area, region, or administrative unit contains or is served by a primary settlement or population hub.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2565ded588190a27319aaa0130b4f |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.