Triple
T16327776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Morrison |
E396468
|
entity |
| Predicate | twitterUsername |
P2943
|
FINISHED |
| Object |
Matt_Morrison
Matt Morrison is an American actor, dancer, and singer best known for his role as Will Schuester on the television series "Glee."
|
E1207377
|
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_Morrison | Statement: [Matthew Morrison, twitterUsername, Matt_Morrison]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt_Morrison Context triple: [Matthew Morrison, twitterUsername, Matt_Morrison]
-
A.
Matt
Matt is a common masculine given name, often short for Matthew, used in many English-speaking countries.
-
B.
Matt
Matt is the given name of Canadian-American actor Matt Frewer, best known for portraying the 1980s television character Max Headroom.
-
C.
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.
-
D.
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.
-
E.
Matt Madalon
Matt Madalon is an American lacrosse coach best known for leading the Princeton University men's lacrosse program.
- 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_Morrison Triple: [Matthew Morrison, twitterUsername, Matt_Morrison]
Generated description
Matt Morrison is an American actor, dancer, and singer best known for his role as Will Schuester on the television series "Glee."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matt_Morrison Target entity description: Matt Morrison is an American actor, dancer, and singer best known for his role as Will Schuester on the television series "Glee."
-
A.
Matt
Matt is a common masculine given name, often short for Matthew, used in many English-speaking countries.
-
B.
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.
-
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 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.
-
E.
Matt Madalon
Matt Madalon is an American lacrosse coach best known for leading the Princeton University men's lacrosse program.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4dcd034819081d849003d918245 |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00260f487c81909e3e54e47c11b83a |
completed | May 10, 2026, 6:30 a.m. |
| NEDg | Description generation | batch_6a0027f09b588190b71d550d2a14868d |
completed | May 10, 2026, 6:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a002899c8888190be247f5db60552e0 |
completed | May 10, 2026, 6:41 a.m. |
Created at: April 10, 2026, 5:07 a.m.