Triple
T6008993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summit of La Francophonie |
E133783
|
entity |
| Predicate | hasAttendeeCategory |
P65012
|
FINISHED |
| Object | observer state |
—
|
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: observer state | Statement: [Summit of La Francophonie, hasAttendeeCategory, observer state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAttendeeCategory Context triple: [Summit of La Francophonie, hasAttendeeCategory, observer state]
-
A.
hasCheckInCategory
Indicates that an entity is associated with a specific category or type of check-in event.
-
B.
hasAttendanceType
chosen
Indicates the specific category or mode of attendance associated with an event or participant (e.g., in-person, virtual, hybrid).
-
C.
hasStudentCategory
Indicates that an entity is classified under a specific category or type of student.
-
D.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
E.
hasEnlistedCategory
Indicates that an entity is associated with a specific enlisted classification or category within an organization or system.
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f4e27a881909cc3f7fef62abc3b |
completed | March 22, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69c049e4daf4819099bf870dc700e0a2 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:06 p.m.