Triple
T23032342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | After Life |
E573496
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Matt
Matt is a supporting character in the dark comedy-drama series "After Life," contributing to the show's exploration of grief, relationships, and personal growth.
|
E1566022
|
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 | Statement: [After Life, hasCharacter, Matt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Context triple: [After Life, hasCharacter, Matt]
-
A.
Matt
Matt is the given name of Matt Eberflus, an American football coach best known as the head coach of the Chicago Bears in the NFL.
-
B.
Matt
Matt is a fictional character from the dark comedy film "The Opposite of Sex," which follows the chaotic fallout of a manipulative teenager’s impact on the lives of those around her.
-
C.
Matt
Matt is the given name of Canadian-American actor Matt Frewer, best known for portraying the 1980s television character Max Headroom.
-
D.
Matt
Matt is a common masculine given name, often short for Matthew, used in many English-speaking countries.
-
E.
Matt
Matt is the idealistic young romantic lead in the long-running musical "The Fantasticks," whose journey explores love, disillusionment, and maturity.
- 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 Triple: [After Life, hasCharacter, Matt]
Generated description
Matt is a supporting character in the dark comedy-drama series "After Life," contributing to the show's exploration of grief, relationships, and personal growth.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matt Target entity description: Matt is a supporting character in the dark comedy-drama series "After Life," contributing to the show's exploration of grief, relationships, and personal growth.
-
A.
Matt
Matt is the given name of Matt Eberflus, an American football coach best known as the head coach of the Chicago Bears in the NFL.
-
B.
Matt
Matt is a fictional character from the dark comedy film "The Opposite of Sex," which follows the chaotic fallout of a manipulative teenager’s impact on the lives of those around her.
-
C.
Matt
Matt is the given name of Canadian-American actor Matt Frewer, best known for portraying the 1980s television character Max Headroom.
-
D.
Matt
Matt is a common masculine given name, often short for Matthew, used in many English-speaking countries.
-
E.
Matt
Matt is the idealistic young romantic lead in the long-running musical "The Fantasticks," whose journey explores love, disillusionment, and maturity.
- 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_69e245b911188190bc3d96326c847969 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f184822a90819081907d72c76770b0 |
completed | April 29, 2026, 4:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bf2b54b888190b1761586d2a2583a |
completed | May 19, 2026, 5:18 a.m. |
| NEDg | Description generation | batch_6a0bf6f8ea048190af15e0494c19c6a1 |
completed | May 19, 2026, 5:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bf76284988190ac4b8f08859aecc6 |
completed | May 19, 2026, 5:38 a.m. |
Created at: April 17, 2026, 3:53 p.m.