Triple
T20818430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoggle |
E512506
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Shari Weiser |
—
|
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: Shari Weiser | Statement: [Hoggle, portrayedBy, Shari Weiser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shari Weiser Context triple: [Hoggle, portrayedBy, Shari Weiser]
-
A.
Shari Weiser
chosen
Shari Weiser is a puppeteer and performer best known for physically portraying the character Hoggle in Jim Henson’s fantasy film "Labyrinth."
-
B.
Shari McMahan
Shari McMahan is an American academic administrator and former provost who serves as the president of Eastern Washington University.
-
C.
Julie Weiss
Julie Weiss is an acclaimed American costume designer known for her work in film, television, and theater, including multiple Academy Award–nominated productions.
-
D.
Deborah Schindler
Deborah Schindler is a film producer best known for her work on the 2003 drama "Mona Lisa Smile."
-
E.
Susan Weiler
Susan Weiler is a prominent landscape architect and design leader known for her influential work with the firm OLIN on major public and urban spaces.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f5b1e08190a9c26f76bd544b68 |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:41 p.m.