Triple
T28480000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VIII Legislatura de España |
E720665
|
entity |
| Predicate | tipoDeCortes |
P165449
|
FINISHED |
| Object | Cortes Generales |
—
|
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: Cortes Generales | Statement: [VIII Legislatura de España, tipoDeCortes, Cortes Generales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tipoDeCortes Context triple: [VIII Legislatura de España, tipoDeCortes, Cortes Generales]
-
A.
isCutInto
Indicates that one entity is divided or separated into pieces or segments that become the other entity.
-
B.
hasTypicalCut
Indicates that one entity is characterized by or associated with a standard or typical type of cut of another entity.
-
C.
cuttingStyle
Indicates the manner or technique in which something is cut or shaped.
-
D.
bladeType
Indicates the specific kind or category of blade associated with an object or entity.
-
E.
coneType
Indicates the specific category or style of cone associated with an entity (e.g., type, shape, or design of the cone).
- F. None of above. chosen
Provenance (4 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_69f01a5983f48190b7c1b8857245a4f7 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f659355a208190be2609ffc7a9c427 |
completed | May 2, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f65875030881909007c502b7dcc998 |
completed | May 2, 2026, 8:03 p.m. |
Created at: April 28, 2026, 2:54 a.m.