Triple
T20053614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zach Cherry |
E499267
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | Duncanville |
—
|
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: Duncanville | Statement: [Zach Cherry, appearedIn, Duncanville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Duncanville Context triple: [Zach Cherry, appearedIn, Duncanville]
-
A.
Duncanville
Duncanville is a suburban city in the Dallas–Fort Worth metropolitan area of North Texas.
-
B.
Duncanville
chosen
Duncanville is an animated sitcom that follows the life of an average teenage boy and his eccentric family in a suburban town.
-
C.
Conroe
Conroe is a city in southeastern Texas, United States, located north of Houston and known for its rapid growth and proximity to Lake Conroe.
-
D.
Grand Prairie
Grand Prairie is a mid-sized suburban city in the Dallas–Fort Worth metropolitan area known for its family attractions, parks, and growing residential communities.
-
E.
Coppell
Coppell is a suburban city in the Dallas–Fort Worth metropolitan area known for its affluent residential neighborhoods and strong public school system.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6633043a481908359ad232607182a |
completed | April 20, 2026, 5:32 p.m. |
Created at: April 11, 2026, 3:38 p.m.