Triple
T14106003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LCI |
E339505
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | BFM TV |
E1074546
|
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: BFM TV | Statement: [LCI, competitor, BFM TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BFM TV Context triple: [LCI, competitor, BFM TV]
-
A.
BFM TV
chosen
BFM TV is a major French 24-hour rolling news television channel known for live coverage of national and international events.
-
B.
BFM
BFM is the IATA airport code for Mobile Downtown Airport, a public airport serving the Mobile, Alabama area.
-
C.
BFM Jazz
BFM Jazz is an independent jazz record label known for producing and promoting contemporary jazz artists and ensembles.
-
D.
FM4
FM4 is an Austrian national radio station known for its alternative music programming and youth-oriented cultural content.
-
E.
Bloomberg Radio
Bloomberg Radio is a 24-hour business and financial news radio network operated by Bloomberg L.P., featuring market updates, economic analysis, and interviews with industry leaders.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de600ada808190b92d67dc30f13d15 |
completed | April 14, 2026, 3:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0b48e448190b4fb8cb33e5d97e6 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:22 p.m.