Triple
T7791781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Warden |
E180195
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
The Bad News Bears
The Bad News Bears is a 1976 sports comedy film about a misfit Little League baseball team and their gruff, down-on-his-luck coach.
|
E693867
|
NE FINISHED |
How this triple was built (4 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: The Bad News Bears | Statement: [Jack Warden, notableWork, The Bad News Bears]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Bad News Bears Context triple: [Jack Warden, notableWork, The Bad News Bears]
-
A.
Touchdown the Bear
Touchdown the Bear is the costumed bear mascot who represents Cornell University's Big Red athletic teams, especially at football games.
-
B.
Buddies
Buddies is a 2012 Indian Malayalam-language comedy film known for its lighthearted storyline and ensemble cast.
-
C.
Babe
Babe is the famous nickname of George Herman "Babe" Ruth, the legendary American baseball player widely regarded as one of the greatest hitters in the sport's history.
-
D.
Babe
Babe is a critically acclaimed 1995 family film that blends live-action and animatronics to tell the story of a pig who aspires to be a sheepdog.
-
E.
Babe
"Babe" is a novel by American author Marianne Wiggins, known for its inventive narrative voice and exploration of complex personal relationships.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: The Bad News Bears Triple: [Jack Warden, notableWork, The Bad News Bears]
Generated description
The Bad News Bears is a 1976 sports comedy film about a misfit Little League baseball team and their gruff, down-on-his-luck coach.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Bad News Bears Target entity description: The Bad News Bears is a 1976 sports comedy film about a misfit Little League baseball team and their gruff, down-on-his-luck coach.
-
A.
Touchdown the Bear
Touchdown the Bear is the costumed bear mascot who represents Cornell University's Big Red athletic teams, especially at football games.
-
B.
Buddies
Buddies is a 2012 Indian Malayalam-language comedy film known for its lighthearted storyline and ensemble cast.
-
C.
Babe
Babe is the famous nickname of George Herman "Babe" Ruth, the legendary American baseball player widely regarded as one of the greatest hitters in the sport's history.
-
D.
Babe
Babe is a critically acclaimed 1995 family film that blends live-action and animatronics to tell the story of a pig who aspires to be a sheepdog.
-
E.
Babe
"Babe" is a novel by American author Marianne Wiggins, known for its inventive narrative voice and exploration of complex personal relationships.
- F. None of above. chosen
Provenance (5 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae9375dcc8190a6cb696c02aeceb7 |
completed | March 30, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb13cdb4288190ae3cfe1ee4e3e496 |
completed | March 31, 2026, 12:22 a.m. |
| NEDg | Description generation | batch_69cb1636b0d48190a57c2d3a7b3b41ed |
completed | March 31, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a29d2988190bb64aada0d2ef463 |
completed | March 31, 2026, 12:49 a.m. |
Created at: March 30, 2026, 4:30 p.m.