Triple
T21510579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kent |
E530706
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Frenchy |
—
|
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: Frenchy | Statement: [Kent, associatedWith, Frenchy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frenchy Context triple: [Kent, associatedWith, Frenchy]
-
A.
Frenchy
Frenchy is the sharp-tongued, seductive saloon singer and gambler famously portrayed by Marlene Dietrich in the classic Western film "Destry Rides Again."
-
B.
Frenchy
Frenchy is a central character in the cult musical fantasy film "Forbidden Zone," known for its surreal, avant-garde style and bizarre underground kingdom setting.
-
C.
Frenchy
chosen
Frenchy is a bubbly, pink-haired beauty school dropout and member of the Pink Ladies in the musical Grease.
-
D.
Frenchie
Frenchie is a resourceful and eccentric member of the vigilante group in the TV series "The Boys," known for his combat skills, improvisational tactics, and complex moral compass.
-
E.
Feeny
Feeny is a small village in County Londonderry, Northern Ireland, situated within the Causeway Coast and Glens district.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea84dfbc8190a23d9a7d6eb2c2b5 |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:25 p.m.