Triple
T12425623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expend4bles |
E296890
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Kenny Gage
Kenny Gage is a film director and screenwriter known for his work in action and thriller movies.
|
E993002
|
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: Kenny Gage | Statement: [Expend4bles, hasCastMember, Kenny Gage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenny Gage Context triple: [Expend4bles, hasCastMember, Kenny Gage]
-
A.
Kevin Gage
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
-
B.
Darren Lemke
Darren Lemke is an American screenwriter and film producer known for working on fantasy and adventure films such as Jack the Giant Slayer and the Goosebumps movie adaptation.
-
C.
Chris Garver
Chris Garver is a renowned American tattoo artist best known for his influential role on television tattoo competitions and his highly detailed, illustrative tattoo work.
-
D.
Gregg Garrison
Gregg Garrison was an American television producer and director best known for his work on variety and music programs during the early decades of TV.
-
E.
Jason Geter
Jason Geter is an American music executive and entrepreneur best known for managing rapper T.I. and helping build the Grand Hustle brand in hip-hop.
- 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: Kenny Gage Triple: [Expend4bles, hasCastMember, Kenny Gage]
Generated description
Kenny Gage is a film director and screenwriter known for his work in action and thriller movies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kenny Gage Target entity description: Kenny Gage is a film director and screenwriter known for his work in action and thriller movies.
-
A.
Kevin Gage
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
-
B.
Darren Lemke
Darren Lemke is an American screenwriter and film producer known for working on fantasy and adventure films such as Jack the Giant Slayer and the Goosebumps movie adaptation.
-
C.
Chris Garver
Chris Garver is a renowned American tattoo artist best known for his influential role on television tattoo competitions and his highly detailed, illustrative tattoo work.
-
D.
Gregg Garrison
Gregg Garrison was an American television producer and director best known for his work on variety and music programs during the early decades of TV.
-
E.
Jason Geter
Jason Geter is an American music executive and entrepreneur best known for managing rapper T.I. and helping build the Grand Hustle brand in hip-hop.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d7b6bd08190b30beba393a5b1e7 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ea44a808190af2c5a6633120814 |
completed | May 2, 2026, 8:29 p.m. |
| NEDg | Description generation | batch_69f661369d608190b7b4f8b2bcf6e9b3 |
completed | May 2, 2026, 8:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f661b369fc81909ced522d7057589e |
completed | May 2, 2026, 8:42 p.m. |
Created at: April 8, 2026, 9:55 p.m.