Triple
T32140828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mil y una muertes |
E820896
|
entity |
| Predicate | hasPoliticalReflection |
P109963
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mil y una muertes, hasPoliticalReflection, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliticalReflection Context triple: [Mil y una muertes, hasPoliticalReflection, true]
-
A.
reflectsPoliticalViewsOf
Indicates that one entity’s opinions, statements, or representations express or mirror the political views held by another entity.
-
B.
reflectsPoliticalEngagement
Indicates that one entity’s behavior, expression, or state demonstrates or reveals its level or nature of involvement in political processes or activities.
-
C.
usesPoliticalCommentary
Indicates that an entity incorporates or employs political commentary within its content, actions, or communications.
-
D.
hasPoliticalDialogue
Indicates that there is an exchange or interaction between entities involving political topics, issues, or negotiations.
-
E.
hasPoliticalComponent
chosen
Indicates that something includes, involves, or is influenced by political factors, interests, or considerations.
- 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_69f349039e0c819091c7a7d322e3f46d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe8f74748c8190bd14a856c057f9f7 |
completed | May 9, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_69fe8e7ed8088190929e0df67aca4de9 |
completed | May 9, 2026, 1:31 a.m. |
Created at: May 1, 2026, 12:30 a.m.