Triple
T3215783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France 4 |
E67390
|
entity |
| Predicate | hasSisterChannel |
P6991
|
FINISHED |
| Object | France 3 |
E68669
|
NE 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: France 3 | Statement: [France 4, hasSisterChannel, France 3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: France 3 Context triple: [France 4, hasSisterChannel, France 3]
-
A.
France 3
chosen
France 3 is a French public television channel known for its regional programming and news coverage as part of the France Télévisions group.
-
B.
France 2
France 2 is a major French public television channel that forms part of the France Télévisions group and broadcasts a wide range of news, entertainment, and cultural programming nationwide.
-
C.
France 4
France 4 is a French public television channel, part of the France Télévisions group, known for broadcasting youth-oriented and family entertainment programming.
-
D.
France 5
France 5 is a French public television channel known for its focus on educational, cultural, and documentary programming.
-
E.
france.tv
france.tv is the official online streaming and catch-up TV platform of the French public broadcaster France Télévisions, offering live channels and on-demand programs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adab096b588190b22e41a76263ae92 |
completed | March 8, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e826c50c8190a6e472e7a8862df2 |
completed | March 12, 2026, 4:21 p.m. |
Created at: March 8, 2026, 3:07 p.m.