Triple
T117931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prime Minister of France |
E2382
|
entity |
| Predicate | officeHoldersMust |
P2718
|
FINISHED |
| Object | be French citizens |
—
|
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: be French citizens | Statement: [Prime Minister of France, officeHoldersMust, be French citizens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHoldersMust Context triple: [Prime Minister of France, officeHoldersMust, be French citizens]
-
A.
officeHoldersMustBe
chosen
Indicates that individuals who hold a particular office are required to possess a specified status, qualification, or characteristic.
-
B.
officeHoldersCollectively
Indicates that a group of individuals jointly hold, or have held, a particular office or set of offices as a collective body.
-
C.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
D.
officeHolderUsually
Indicates that an entity is the person who typically or customarily holds a particular office or position.
-
E.
officeHoldersNumber
Indicates the number of individuals who hold a particular office or position.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a258e0b11c8190b7b5cf3c354c47ce |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25646d5088190a057989c32da3a90 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.