Triple
T36921414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MK2 Diffusion |
E913209
|
entity |
| Predicate | handlesFrenchReleaseOf |
P186748
|
FINISHED |
| Object | Three Colors: Blue |
—
|
NE NERFINISHED |
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: Three Colors: Blue | Statement: [MK2 Diffusion, handlesFrenchReleaseOf, Three Colors: Blue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: handlesFrenchReleaseOf Context triple: [MK2 Diffusion, handlesFrenchReleaseOf, Three Colors: Blue]
-
A.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
B.
containsFrenchPhrases
Indicates that the subject includes one or more phrases expressed in the French language.
-
C.
hasFrenchSector
Indicates that an entity includes, controls, or is associated with a sector or area designated as French.
-
D.
usesPrimaryFrenchGateway
Indicates that an entity routes its primary communications or connections through a main gateway located in or associated with French infrastructure or networks.
-
E.
reservedToFrance
Indicates that something is exclusively allocated or designated for France.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fa0a799b9081909bfa8293a22c4b00 |
completed | May 5, 2026, 3:19 p.m. |
Created at: May 3, 2026, 4:13 p.m.