Triple
T32073444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Force de frappe |
E819077
|
entity |
| Predicate | hasFormerComponent |
P193318
|
FINISHED |
| Object | French land-based nuclear forces |
—
|
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 land-based nuclear forces | Statement: [Force de frappe, hasFormerComponent, French land-based nuclear forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerComponent Context triple: [Force de frappe, hasFormerComponent, French land-based nuclear forces]
-
A.
hasFormerParent
Indicates that an entity was previously the parent of another entity but no longer holds that parental role or status.
-
B.
hasFormerEntity
Indicates that one entity previously existed in a different form, role, or identity that is represented by another entity.
-
C.
hasFormerType
Indicates that an entity previously had a certain type or classification that has since changed.
-
D.
hasFormerEvent
Indicates that an entity was preceded by a specific earlier event in its history or sequence.
-
E.
hasFormerSection
chosen
Indicates that an entity previously contained another entity as a section or subdivision, but no longer does so in its current structure.
- 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: May 1, 2026, 12:23 a.m.