Triple
T3137355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuck Noll |
E65564
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Chuck |
E79215
|
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: Chuck | Statement: [Chuck Noll, nickname, Chuck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chuck Context triple: [Chuck Noll, nickname, Chuck]
-
A.
Chuck
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.
-
B.
Chuck
chosen
Chuck is a common diminutive form of the given name Charles, often used as a familiar or informal nickname.
-
C.
Charlie
Charlie is Dory’s loving but forgetful father in the animated film "Finding Dory," known for his patience, optimism, and inventive ways of helping her cope with memory loss.
-
D.
Charlie
Charlie was the third nuclear test in the U.S. Operation Crossroads series, planned as an underwater detonation to study the effects of nuclear weapons on naval vessels.
-
E.
Charlie
Charlie is the fictional Boston subway rider in the folk song "Charlie on the MTA," known for being unable to get off the train because he lacks the fare to exit.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada574509c81908a88bb10ea35516d |
completed | March 8, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f8a1a2081909081c36075d4ddbe |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:05 p.m.