Triple
T35993263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1933 Spanish general election |
E1040906
|
entity |
| Predicate | regionWithStrongLeftVote |
P162847
|
FINISHED |
| Object | Asturias |
—
|
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: Asturias | Statement: [1933 Spanish general election, regionWithStrongLeftVote, Asturias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionWithStrongLeftVote Context triple: [1933 Spanish general election, regionWithStrongLeftVote, Asturias]
-
A.
regionWithStrongBlocSupport
chosen
Indicates that a geographic region exhibits notably high or concentrated support for a particular political bloc or alliance.
-
B.
strongestSupportRegion
Indicates the region where an entity receives its highest level of support compared to all other regions.
-
C.
regionOfStrongOpposition
Indicates that one entity is a geographic or conceptual area where there is significant resistance or disagreement toward another entity or its actions.
-
D.
votingRegion
Indicates the geographic or administrative area in which an entity is eligible or authorized to vote.
-
E.
regionalVote
Indicates that an entity participates in or is associated with a voting process specific to a particular geographic region.
- 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_69f76e29084c819083987b828d414de7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a000014497c819088d5cda3977522dd |
completed | May 10, 2026, 3:48 a.m. |
| PD | Predicate disambiguation | batch_69ffff9a52b08190be1024e0fb6fe661 |
completed | May 10, 2026, 3:46 a.m. |
Created at: May 3, 2026, 4:07 p.m.