Triple
T8005092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy Prime Minister of the United Arab Emirates |
E186344
|
entity |
| Predicate | numberOfCurrentOfficeHolders |
P3416
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Deputy Prime Minister of the United Arab Emirates, numberOfCurrentOfficeHolders, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCurrentOfficeHolders Context triple: [Deputy Prime Minister of the United Arab Emirates, numberOfCurrentOfficeHolders, 3]
-
A.
officeHoldersNumber
chosen
Indicates the number of individuals who hold a particular office or position.
-
B.
firstOfficeHoldersCount
Indicates the number of individuals who initially held a particular office or position.
-
C.
officeHolderCountIncludes
Indicates that a specified count or total explicitly includes the number of individuals holding a particular office or position.
-
D.
officeHoldersNumbered
Indicates that a specific office or position has its holders identified and distinguished by assigned numbers (e.g., first holder, second holder, etc.).
-
E.
officeHolders
Indicates a relationship where one or more entities hold, or have held, an official position or role within a specified organization, institution, or jurisdiction.
- 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3cf5fb588190ada4ec7d8087619c |
completed | March 31, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:18 p.m.