Triple
T14114307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1996 Japanese general election |
E339721
|
entity |
| Predicate | numberOfPRBlocks |
P112870
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [1996 Japanese general election, numberOfPRBlocks, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPRBlocks Context triple: [1996 Japanese general election, numberOfPRBlocks, 11]
-
A.
numberOfBlocks
Indicates the quantity of discrete block units associated with or contained by a given entity.
-
B.
numberOfCellBlocks
Indicates the total count of distinct cell blocks associated with or contained within a given entity.
-
C.
estimatedNumberOfBlocks
Indicates the approximate count of discrete blocks associated with or involved in the given entity or context.
-
D.
numberOfPanels
Indicates the total count of distinct panels associated with or contained within a given entity.
-
E.
numberOfConcretePanels
Indicates the total count of concrete panels associated with or used in relation to a given entity.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de600f992c81908133813f2894dcca |
completed | April 14, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:22 p.m.