Triple
T23305874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Akerlind |
E590431
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Well |
—
|
NE NERFINISHED |
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: Well | Statement: [Christopher Akerlind, notableWork, Well]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Well Context triple: [Christopher Akerlind, notableWork, Well]
-
A.
Well
chosen
Well is a critically acclaimed autobiographical play by Lisa Kron that blends humor and drama to explore themes of illness, identity, and the complexities of mother-daughter relationships.
-
B.
Well
Well is the commonly used nickname for Motherwell Football Club, a professional football team based in Motherwell, Scotland.
-
C.
Good for It
"Good for It" is a track featured on the mixtape "NAV" by Canadian rapper and producer Nav.
-
D.
All Shall Be Well
All Shall Be Well is a choral composition by contemporary British composer Roxanna Panufnik, known for its luminous harmonies and spiritually reflective character.
-
E.
Nice Work
Nice Work is a British television drama adaptation of David Lodge's campus novel, featuring Warren Clarke in a leading role.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1972737c08190bd011776564c3861 |
completed | April 29, 2026, 5:29 a.m. |
Created at: April 17, 2026, 5:05 p.m.