Triple
T1465377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayotte |
E27009
|
entity |
| Predicate | hasStatusSince |
P19818
|
FINISHED |
| Object | French department since 2011 |
—
|
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: French department since 2011 | Statement: [Mayotte, hasStatusSince, French department since 2011]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatusSince Context triple: [Mayotte, hasStatusSince, French department since 2011]
-
A.
currentStatusSince
chosen
Indicates the point in time since which an entity has held its current status or state.
-
B.
hasClockSince
Indicates that an entity has possessed or maintained a clock continuously from a specified point in time onward.
-
C.
hasStatusIn
Indicates that an entity holds or is assigned a particular status within a specified context, scope, or system.
-
D.
hasActivityStatus
Indicates the current state or condition of an activity, such as whether it is planned, ongoing, completed, or cancelled.
-
E.
observedSince
Indicates that one entity has been continuously or repeatedly observed starting from a specified point in time.
- 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_69a4c5ba2d5c81909ee85713de961fcb |
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.