Triple
T10553778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beauty Shop |
E249021
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Mena Suvari |
E332875
|
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: Mena Suvari | Statement: [Beauty Shop, stars, Mena Suvari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mena Suvari Context triple: [Beauty Shop, stars, Mena Suvari]
-
A.
Mena Suvari
chosen
Mena Suvari is an American actress and model best known for her breakout role in the acclaimed film "American Beauty" and her work in the "American Pie" series.
-
B.
Rachael Leigh Cook
Rachael Leigh Cook is an American actress and producer best known for her breakout role in the 1999 teen romantic comedy film "She's All That."
-
C.
Rose McGowan
Rose McGowan is an American actress and activist best known for her roles in the TV series "Charmed" and films like "Scream" and "Jawbreaker," as well as for her prominent involvement in the #MeToo movement.
-
D.
Nicole Kassell
Nicole Kassell is an American film and television director and producer known for her work on acclaimed series such as Watchmen and The Leftovers.
-
E.
Dedee Pfeiffer
Dedee Pfeiffer is an American actress known for her roles in 1980s and 1990s film and television, including the cult horror-comedy "Vamp."
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d527118da081909ca61bc555a17609 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b3148dc81908720c27e58a325ab |
completed | April 10, 2026, 7:10 p.m. |
Created at: April 6, 2026, 12:34 p.m.