Triple
T10445005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricky Jay |
E246263
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | State and Main |
E649032
|
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: State and Main | Statement: [Ricky Jay, appearedIn, State and Main]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: State and Main Context triple: [Ricky Jay, appearedIn, State and Main]
-
A.
State and Main
chosen
State and Main is a satirical comedy film about a Hollywood production disrupting life in a small New England town.
-
B.
The State
"The State" is a foundational political science text by Woodrow Wilson that analyzes the nature, functions, and evolution of government and political institutions.
-
C.
The State
The State is an American sketch comedy troupe best known for its influential 1990s MTV series featuring an ensemble of future prominent comedians.
-
D.
State
State is an underground subway station in downtown Boston that serves as a major transfer point between the MBTA Blue and Orange Lines.
-
E.
State
State is a behavioral design pattern that lets an object alter its behavior when its internal state changes, making it appear as if the object has changed its class.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fdbf81508190a160edea85105d3a |
completed | April 7, 2026, 12:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87eeae8788190b63534fa4f942ead |
completed | April 10, 2026, 4:39 a.m. |
Created at: April 6, 2026, 12:16 p.m.