Triple
T700435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French |
E13984
|
entity |
| Predicate | isOfficialInMultipleContinents |
P18403
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [French, isOfficialInMultipleContinents, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOfficialInMultipleContinents Context triple: [French, isOfficialInMultipleContinents, true]
-
A.
areOfficialIn
Indicates that an entity holds an official role, position, or capacity within another entity (such as an organization, institution, or jurisdiction).
-
B.
isInternational
Indicates that something has a connection to, involves, or extends across more than one country.
-
C.
underlyingIsMultinational
Indicates that the underlying entity operates in or is registered across multiple countries as a multinational organization.
-
D.
hasOfficial
Indicates that an entity is formally associated with, represented by, or served by a designated official or office-holder.
-
E.
hasOverseasPresenceIn
Indicates that an entity maintains operations, offices, or activities in a foreign country or region.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a544e3608190ac315c7aa9f88e7e |
completed | March 1, 2026, 8:44 p.m. |
| PD | Predicate disambiguation | batch_69a4a4ec8c748190b198492a0eea4445 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a54235548190b46218ea18f77341 |
completed | March 1, 2026, 8:44 p.m. |
Created at: March 1, 2026, 7:36 p.m.