Triple
T21349919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Derwin |
E526446
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Chuck |
—
|
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: Chuck | Statement: [Mark Derwin, notableWork, Chuck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chuck Context triple: [Mark Derwin, notableWork, Chuck]
-
A.
Chuck
Chuck is a common diminutive form of the given name Charles, often used as a familiar or informal nickname.
-
B.
Chuck
chosen
Chuck is an American action-comedy television series that blends spy drama with workplace humor, centered on an ordinary computer geek who accidentally becomes a government asset.
-
C.
Charlie
Charlie is the yellow-suited captain and one of the three main playable leaders in Pikmin 3, known for commanding Pikmin on the planet PNF-404.
-
D.
Charlie
Charlie is a character featured in the work titled "Seascape."
-
E.
Charlie
Charlie is the reclusive, morbidly obese English professor at the center of Darren Aronofsky’s film "The Whale," whose struggle with grief, guilt, and self-destruction drives the story’s emotional core.
- 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_69e0b51cd5cc81909ac1187971e8a8ad |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8ad30512081909012ce318fa67679 |
completed | April 22, 2026, 11:12 a.m. |
Created at: April 16, 2026, 5:03 p.m.