Triple
T10470579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dante's Peak |
E246911
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Elizabeth Hoffman |
E394003
|
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: Elizabeth Hoffman | Statement: [Dante's Peak, castMember, Elizabeth Hoffman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Hoffman Context triple: [Dante's Peak, castMember, Elizabeth Hoffman]
-
A.
Elizabeth Hoffman
chosen
Elizabeth Hoffman is an American actress best known for her roles in the television series "St. Elsewhere" and the film "Dante's Peak."
-
B.
Elizabeth Hofmann
Elizabeth Hofmann is known as the spouse of American glass artist and sculptor Dan Dailey.
-
C.
Astrid Hofferson
Astrid Hofferson is a brave and skilled Viking warrior and dragon rider from the "How to Train Your Dragon" franchise, known as Hiccup's close friend and eventual love interest.
-
D.
Rachel Buchman
Rachel Buchman is the titular bride and central figure in the 2008 drama film "Rachel Getting Married," around whose wedding and family tensions the story revolves.
-
E.
Emma Flegenheimer
Emma Flegenheimer was the mother of notorious American mobster Dutch Schultz (born Arthur Flegenheimer).
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509305fec81908b1acd91ae1f875d |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8a0094910819094d492c87b31898e |
completed | April 10, 2026, 7 a.m. |
Created at: April 6, 2026, 12:20 p.m.