Triple
T12438566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chronicle |
E297210
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Matt Garetty
Matt Garetty is the telekinetic teenage protagonist of the 2012 found-footage science fiction film "Chronicle," whose growing powers lead him down a dark and destructive path.
|
E983961
|
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: Matt Garetty | Statement: [Chronicle, mainCharacter, Matt Garetty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Garetty Context triple: [Chronicle, mainCharacter, Matt Garetty]
-
A.
Guy Burchett
Guy Burchett was a young motorcycle courier for Elton John’s record label whose untimely death inspired Elton John’s instrumental piece "Song for Guy."
-
B.
Kevin Gage
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
-
C.
Joe Gayton
Joe Gayton is an American screenwriter and producer best known for co-creating the Western television drama series "Hell on Wheels."
-
D.
Matt Curtis
Matt Curtis is a cinematographer known for his work on the film "Amy."
-
E.
Matt Hulett
Matt Hulett is an American technology and business executive known for leading and scaling multiple software and digital media companies.
- 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: Matt Garetty Triple: [Chronicle, mainCharacter, Matt Garetty]
Generated description
Matt Garetty is the telekinetic teenage protagonist of the 2012 found-footage science fiction film "Chronicle," whose growing powers lead him down a dark and destructive path.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matt Garetty Target entity description: Matt Garetty is the telekinetic teenage protagonist of the 2012 found-footage science fiction film "Chronicle," whose growing powers lead him down a dark and destructive path.
-
A.
Guy Burchett
Guy Burchett was a young motorcycle courier for Elton John’s record label whose untimely death inspired Elton John’s instrumental piece "Song for Guy."
-
B.
Kevin Gage
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
-
C.
Joe Gayton
Joe Gayton is an American screenwriter and producer best known for co-creating the Western television drama series "Hell on Wheels."
-
D.
Matt Curtis
Matt Curtis is a cinematographer known for his work on the film "Amy."
-
E.
Matt Hulett
Matt Hulett is an American technology and business executive known for leading and scaling multiple software and digital media companies.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d8dc0f881908a3da736d8947ce1 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f0911a08190ba84a20950762e68 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f640ef7dd08190bf78d04cffac1a44 |
completed | May 2, 2026, 6:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f641abe114819093d99a327f2220c2 |
completed | May 2, 2026, 6:25 p.m. |
Created at: April 8, 2026, 9:55 p.m.