Triple
T1467402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Co-Prince of Andorra |
E27055
|
entity |
| Predicate | numberOfOfficeHoldersSimultaneously |
P3416
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Co-Prince of Andorra, numberOfOfficeHoldersSimultaneously, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfOfficeHoldersSimultaneously Context triple: [Co-Prince of Andorra, numberOfOfficeHoldersSimultaneously, 2]
-
A.
firstOfficeHoldersCount
Indicates the number of individuals who initially held a particular office or position.
-
B.
officeHoldersNumber
chosen
Indicates the number of individuals who hold a particular office or position.
-
C.
officeHoldersNumbered
Indicates that a specific office or position has its holders identified and distinguished by assigned numbers (e.g., first holder, second holder, etc.).
-
D.
officeHoldersAreUsually
Indicates that individuals holding a particular office or position are typically or generally characterized by a specified property or role.
-
E.
officeHoldersCollectively
Indicates that a group of individuals jointly hold, or have held, a particular office or set of offices as a collective 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5bcfa0881909d6137c69825bc7a |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48121e48190946c23c583e5fb64 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.