Triple
T16205053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How the Grinch Stole Christmas! The Musical |
E393303
|
entity |
| Predicate | hasSetting |
P3538
|
FINISHED |
| Object | Whoville |
E374994
|
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: Whoville | Statement: [How the Grinch Stole Christmas! The Musical, hasSetting, Whoville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Whoville Context triple: [How the Grinch Stole Christmas! The Musical, hasSetting, Whoville]
-
A.
Whoville
chosen
Whoville is a whimsical, tiny town inhabited by the Whos in Dr. Seuss’s stories, notably featured in both "Horton Hears a Who!" and "How the Grinch Stole Christmas!"
-
B.
Snickersville
Snickersville was the historic name of the rural village now known as Bluemont in Loudoun County, Virginia.
-
C.
Toonerville
Toonerville is the fictional small-town setting featured in the early 20th-century Mickey McGuire comedy stories and film shorts.
-
D.
Snowville
Snowville is a small rural settlement located within the township of Tehkummah in Ontario, Canada.
-
E.
Maxville
Maxville is a small unincorporated community located in the state of Missouri in the United States.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2270d6e5c8190aee4bcca76cbe47c |
completed | April 17, 2026, 12:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d9c35248190a5540a692503c989 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 5:03 a.m.