Triple
T15909989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Girlie Show |
E385819
|
entity |
| Predicate | employerOf |
P7
|
FINISHED |
| Object | Cerie |
E385821
|
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: Cerie | Statement: [The Girlie Show, employerOf, Cerie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cerie Context triple: [The Girlie Show, employerOf, Cerie]
-
A.
Cerie
chosen
Cerie is a young, attractive assistant at the fictional TV show on the sitcom "30 Rock," known for her laid-back attitude and comedic interactions with Liz Lemon.
-
B.
Rhos
Rhos is a village in Neath Port Talbot, Wales, known for its residential character within the Swansea Valley region.
-
C.
Islwyn
Islwyn is a former local government district and historic area in south Wales, named after the River Ebbw and known for its coal-mining heritage.
-
D.
Gwilen
Gwilen is the Breton name for the French river Vilaine, which flows through Brittany in western France.
-
E.
Sirellyn
Sirellyn is a character from Terry Mancour’s Spellmonger fantasy series, known for her role within the intricate political and magical conflicts of that world.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1565ea7a8819097efffda366b5245 |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb05750ac81908860143f4ca26cc7 |
completed | May 9, 2026, 10:08 p.m. |
Created at: April 10, 2026, 4:52 a.m.