Triple
T13036283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Free |
E326567
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | SFR |
E326752
|
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: SFR | Statement: [Free, competitor, SFR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SFR Context triple: [Free, competitor, SFR]
-
A.
SFR
chosen
SFR is a major French telecommunications company providing mobile, internet, and television services.
-
B.
SRF
SRF is the German-language division of the Swiss Broadcasting Corporation, responsible for producing and broadcasting radio, television, and online content in German-speaking Switzerland.
-
C.
SRF
SRF is a French filmmakers' association best known for organizing the Directors' Fortnight sidebar at the Cannes Film Festival and advocating for directors' artistic and professional interests.
-
D.
SFS
SFS is a common abbreviation for Allianz Stadium, a major sports and entertainment venue in Sydney, Australia.
-
E.
SFS
SFS is a renowned Georgetown University school specializing in international affairs, diplomacy, and global policy education.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ead25b7c8190af2ccf26b44c2ea2 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 8:55 p.m.