Triple
T33726606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Netanyahu Government |
E864159
|
entity |
| Predicate | numberOfDeputyMinisters |
P80248
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Second Netanyahu Government, numberOfDeputyMinisters, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDeputyMinisters Context triple: [Second Netanyahu Government, numberOfDeputyMinisters, 9]
-
A.
hasNumberOfMinisters
Indicates the specific count of ministers associated with an entity, such as a government, cabinet, or organization.
-
B.
numberOfMinistries
Indicates the total count of ministries associated with or belonging to a given entity.
-
C.
deputyMinister
Indicates that one entity serves as the deputy minister (second-in-command or subordinate minister) to another entity within a governmental or ministerial hierarchy.
-
D.
hasNumberOfDeputies
chosen
Indicates the specific count of deputies associated with or assigned to an entity.
-
E.
numberOfMinistersLimit
Indicates a constraint specifying the maximum allowable number of ministers in a given context or governing body.
- 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_69f3498a64cc8190b4b414c67b280d93 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0349d158b881908bfbdb501ea565ee |
completed | May 12, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_6a034750e3d48190a88ee3604a36b46d |
completed | May 12, 2026, 3:29 p.m. |
Created at: May 1, 2026, 1:44 a.m.