Triple
T22002558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halloweentown High |
E543366
|
entity |
| Predicate | mainCastMember |
P5563
|
FINISHED |
| Object | Joey Zimmerman |
—
|
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: Joey Zimmerman | Statement: [Halloweentown High, mainCastMember, Joey Zimmerman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joey Zimmerman Context triple: [Halloweentown High, mainCastMember, Joey Zimmerman]
-
A.
Joey Zimmerman
chosen
Joey Zimmerman is an American actor best known for playing Dylan Piper in Disney Channel’s "Halloweentown" film series.
-
B.
Joey Luft
Joey Luft is an American television producer and occasional actor best known as the son of legendary entertainer Judy Garland and producer Sidney Luft.
-
C.
Joey Newman
Joey Newman is an American composer and conductor known for his work on television scores and themes, including contributions to major sports broadcasts.
-
D.
Joey Matthews
Joey Matthews is a central character in the 1954 mystery thriller film "Gorilla at Large," around whom much of the circus-themed suspense and intrigue revolves.
-
E.
Joey Curtis
Joey Curtis is a filmmaker and screenwriter known for his work in independent cinema and visually driven storytelling.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1276bf2a48190910d9c27f1c5e74f |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 16, 2026, 8:20 p.m.