Triple
T6418355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2023 Spanish general election |
E127883
|
entity |
| Predicate | resultCharacterization |
P70548
|
FINISHED |
| Object | highly fragmented parliament |
—
|
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: highly fragmented parliament | Statement: [2023 Spanish general election, resultCharacterization, highly fragmented parliament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resultCharacterization Context triple: [2023 Spanish general election, resultCharacterization, highly fragmented parliament]
-
A.
ruleCharacterization
Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
-
B.
findingCharacterization
Indicates that a finding is being described or classified in terms of its nature, features, or diagnostic significance.
-
C.
scopeCharacterization
Indicates how the extent, boundaries, or coverage of something is defined, described, or qualified in relation to another entity or context.
-
D.
subsequentCharacterization
Indicates that one characterization or description of something occurs later in time than, and in relation to, an earlier characterization of the same thing.
-
E.
trialCharacterization
Indicates the specific features, conditions, or parameters that define and distinguish a particular trial within an experimental or procedural context.
- 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_69c0083815208190a9b299b8e0640218 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c068eb6c988190b54de6182d0f490d |
completed | March 22, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69c060f5d4e481909d1366190607b586 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623e3cd48190929b0e3cba013909 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:42 p.m.