Triple
T13651631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SFR |
E326752
|
entity |
| Predicate | hasCompetitor |
P1375
|
FINISHED |
| Object | Free Mobile |
E326561
|
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: Free Mobile | Statement: [SFR, hasCompetitor, Free Mobile]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Free Mobile Context triple: [SFR, hasCompetitor, Free Mobile]
-
A.
Free Mobile
chosen
Free Mobile is a major French mobile network operator known for disrupting the market with low-cost, no-contract plans.
-
B.
For Free
"For Free" is a reflective folk song by Joni Mitchell that contrasts commercial success with the purity of a street musician’s art.
-
C.
Free
Free is the second studio album by American singer-songwriter Gavin DeGraw, showcasing a more stripped-down, soulful sound compared to his debut.
-
D.
Free
"Free" is a 1994 studio album by American alternative rock band Concrete Blonde, showcasing their dark, melodic rock sound and introspective songwriting.
-
E.
Free
"Free" is a soulful R&B single by British singer Estelle that helped establish her early career and showcase her distinctive vocal style.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc609676c8190b5b1cabe6b315142 |
completed | April 12, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78affa3c481909dba71e2ce9f44c1 |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 9:52 p.m.