Triple
T17135123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vichy French Navy |
E415815
|
entity |
| Predicate | relationshipWithFreeFrench |
P126239
|
FINISHED |
| Object | rival and sometimes opponent |
—
|
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: rival and sometimes opponent | Statement: [Vichy French Navy, relationshipWithFreeFrench, rival and sometimes opponent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithFreeFrench Context triple: [Vichy French Navy, relationshipWithFreeFrench, rival and sometimes opponent]
-
A.
partyRoleOfFrance
Indicates the specific role or capacity that France holds as a party within a given agreement, event, or relationship.
-
B.
joinedFrance
Indicates that an entity became a member of or was incorporated into France.
-
C.
frenchTroopsEvacuated
Indicates that French military forces withdrew or were removed from a particular location or situation.
-
D.
FrenchRole
Indicates a role or position that an entity holds specifically within a French context (e.g., in France or related to French institutions, culture, or language).
-
E.
relationshipToArmandAubigny
Indicates the specific nature of the relationship an entity has with Armand Aubigny.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f02dca8881908efd73741397a207 |
completed | April 18, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69e3830192ac819091344a9e5a36c8c9 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:36 a.m.