Triple
T10216212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurie Metcalf |
E242446
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Matt Roth |
E850685
|
NE FINISHED |
How this triple was built (2 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 Roth | Statement: [Laurie Metcalf, hasRelative, Matt Roth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Roth Context triple: [Laurie Metcalf, hasRelative, Matt Roth]
-
A.
Matt Roth
chosen
Matt Roth is an American actor known for his television work, including recurring roles on the sitcom "Roseanne."
-
B.
Joe Roth
Joe Roth is an American film producer and studio executive who became a prominent sports figure as the lead investor and former majority owner of Major League Soccer’s Seattle Sounders FC.
-
C.
Jeffrey Dean
Jeffrey Dean is a prominent American computer scientist and software engineer best known for his influential work on large-scale distributed systems and infrastructure at Google.
-
D.
Michael Culver
Michael Culver is a British actor known for his character roles in film and television, including appearances in productions such as "A Passage to India" and "The Empire Strikes Back."
-
E.
Mike Vogel
Mike Vogel is an American actor known for his roles in films like "Cloverfield" and "The Help" as well as TV series such as "Under the Dome."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa2894d0819095704449ecc2db6c |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f6f4d0cc8190ae41277b15b3012d |
completed | April 9, 2026, 12:46 a.m. |
Created at: April 6, 2026, 11:05 a.m.