Triple
T16097499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeopardy! |
E390524
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Merv Griffin Enterprises |
E741336
|
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: Merv Griffin Enterprises | Statement: [Jeopardy!, productionCompany, Merv Griffin Enterprises]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merv Griffin Enterprises Context triple: [Jeopardy!, productionCompany, Merv Griffin Enterprises]
-
A.
Merv Griffin Enterprises
chosen
Merv Griffin Enterprises was a television production company best known for creating and producing iconic game shows such as "Jeopardy!" and "Wheel of Fortune."
-
B.
MGM Holdings
MGM Holdings is the parent company that owns and oversees Metro-Goldwyn-Mayer’s entertainment assets and operations.
-
C.
Woods Entertainment
Woods Entertainment is a film production company best known for producing the crime drama movie "Cop Land."
-
D.
MGM
MGM is a major American entertainment and hospitality brand best known for its iconic casinos, resorts, and film studio legacy.
-
E.
MGM
MGM is the IATA airport code for Montgomery Regional Airport, the primary commercial airport serving Montgomery, Alabama.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6551a48190afb7e0c61e22b541 |
completed | April 17, 2026, 9:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff29da7008190aebeb35113e726ef |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 4:59 a.m.