Triple
T4317763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish general election, April 2019 |
E96433
|
entity |
| Predicate | numberOfConstituenciesCongress |
P13200
|
FINISHED |
| Object | 52 |
—
|
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: 52 | Statement: [Spanish general election, April 2019, numberOfConstituenciesCongress, 52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfConstituenciesCongress Context triple: [Spanish general election, April 2019, numberOfConstituenciesCongress, 52]
-
A.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
B.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
-
C.
numberOfStatesRepresented
Indicates how many distinct states are represented or covered in a given context or entity.
-
D.
numberOfLegislativeChambers
Indicates the quantity of distinct legislative chambers that a given political or legislative body possesses.
-
E.
hasNumberOfConstituencies
chosen
Indicates the specific count of constituencies associated with an 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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350f883c88190a2d72f7d124eef43 |
completed | March 12, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69b34f4a07b08190a06ada0d9cbb14fb |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:12 p.m.