Triple
T21814418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eddie Fisher |
E538562
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Carrie Fisher |
—
|
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: Carrie Fisher | Statement: [Eddie Fisher, child, Carrie Fisher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carrie Fisher Context triple: [Eddie Fisher, child, Carrie Fisher]
-
A.
Carrie Fisher
chosen
Carrie Fisher was an American actress and writer best known for her iconic role as Princess Leia in the Star Wars film series.
-
B.
Susan Dey
Susan Dey is an American actress best known for her breakout role as Laurie Partridge on the 1970s television sitcom "The Partridge Family" and later as a lead on the legal drama "L.A. Law."
-
C.
Majel Barrett
Majel Barrett was an American actress and producer best known for her multiple iconic roles and voice work across the Star Trek franchise.
-
D.
Sean Young
Sean Young is an American actress best known for her roles in 1980s films such as "Blade Runner," "Dune," and "No Way Out."
-
E.
Kate Mara
Kate Mara is an American actress known for her roles in films like "The Martian" and "Brokeback Mountain" and TV series such as "House of Cards."
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc8e6808190bde4d0e0981e4117 |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 16, 2026, 6:54 p.m.