Triple
T2771170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cliffhanger |
E61457
|
entity |
| Predicate | leadCharacterName |
P12814
|
FINISHED |
| Object |
Gabe Walker
Gabe Walker is the skilled mountain climber and rescue ranger portrayed by Sylvester Stallone in the action thriller film "Cliffhanger."
|
E296914
|
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: Gabe Walker | Statement: [Cliffhanger, leadCharacterName, Gabe Walker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabe Walker Context triple: [Cliffhanger, leadCharacterName, Gabe Walker]
-
A.
Adam Gibbs
Adam Gibbs is a film producer known for his work on the movie "Love, Antosha."
-
B.
Brant Daugherty
Brant Daugherty is an American actor known for his roles in television series like "Pretty Little Liars" and films including the "Fifty Shades" franchise.
-
C.
Kevin Gage
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
-
D.
Matt Graver
Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
-
E.
Trent Baalke
Trent Baalke is an American football executive best known for his tenure as an NFL general manager, including leading front offices for multiple franchises.
- 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: Gabe Walker Triple: [Cliffhanger, leadCharacterName, Gabe Walker]
Generated description
Gabe Walker is the skilled mountain climber and rescue ranger portrayed by Sylvester Stallone in the action thriller film "Cliffhanger."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gabe Walker Target entity description: Gabe Walker is the skilled mountain climber and rescue ranger portrayed by Sylvester Stallone in the action thriller film "Cliffhanger."
-
A.
Adam Gibbs
Adam Gibbs is a film producer known for his work on the movie "Love, Antosha."
-
B.
Brant Daugherty
Brant Daugherty is an American actor known for his roles in television series like "Pretty Little Liars" and films including the "Fifty Shades" franchise.
-
C.
Kevin Gage
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
-
D.
Matt Graver
Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
-
E.
Trent Baalke
Trent Baalke is an American football executive best known for his tenure as an NFL general manager, including leading front offices for multiple franchises.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd6a23208190ba94c9a9f601a042 |
completed | March 7, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc05061808190abe709eff7a8c986 |
completed | March 10, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69afc0b6f7208190ac4f135ae72f0336 |
completed | March 10, 2026, 6:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc133f8088190bd505db0d0d1d6f7 |
completed | March 10, 2026, 6:59 a.m. |
Created at: March 6, 2026, 9:57 p.m.