Triple
T561466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cortes of Spain |
E13460
|
entity |
| Predicate | usedAsName |
P2506
|
FINISHED |
| Object | historical name for Spain’s national legislature |
—
|
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: historical name for Spain’s national legislature | Statement: [Cortes of Spain, usedAsName, historical name for Spain’s national legislature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsName Context triple: [Cortes of Spain, usedAsName, historical name for Spain’s national legislature]
-
A.
nameUsedIn
Indicates that a particular name is employed or referenced within a specified context, work, or usage setting.
-
B.
nameUsedBy
Indicates that a particular name is employed or referenced by a specific entity.
-
C.
nameUsedToAvoid
Indicates that one entity uses a particular name or designation in order to avoid another entity or an unwanted situation involving that entity.
-
D.
hasGivenNameUsage
Indicates that an entity is associated with a particular way or context in which its given name is used.
-
E.
isUsedAs
chosen
Indicates that one entity serves a particular function, role, or purpose as another entity.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499e2795c8190903240e79964156d |
completed | March 1, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69a494befb8481908bb4e2e9f31e343b |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.