Triple
T17065070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirk Acevedo |
E414062
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object | Carver |
E1220757
|
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: Carver | Statement: [Kirk Acevedo, playedCharacter, Carver]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carver Context triple: [Kirk Acevedo, playedCharacter, Carver]
-
A.
Carver
Carver is a small town in southeastern Massachusetts known for its cranberry bogs and rural character.
-
B.
Carver
Carver is a common shorthand name for Carver-Hawkeye Arena, the University of Iowa’s primary indoor sports venue.
-
C.
Carver
Carver is a surname most notably associated with American short story writer and poet Raymond Carver, a key figure in late 20th-century minimalist fiction.
-
D.
Carver
Carver is the person after whom Carver Glacier in Oregon was named, likely an early explorer or notable figure associated with the region.
-
E.
Carver
chosen
Carver is the relentless former Confederate colonel portrayed by Liam Neeson who hunts Gideon across the American frontier in the 2006 Western thriller "Seraphim Falls."
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db806de48190a9ce68b40fc77a74 |
completed | April 18, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01234e9a94819094618ba43b7d22b4 |
completed | May 11, 2026, 12:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.