Triple
T17252537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dane Clark |
E418791
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Dane Clark |
—
|
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: Dane Clark | Statement: [Dane Clark, name, Dane Clark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dane Clark Context triple: [Dane Clark, name, Dane Clark]
-
A.
Dane Clark
chosen
Dane Clark was an American film and television actor known for his tough, working-class persona in numerous 1940s and 1950s Hollywood dramas and war movies.
-
B.
Matt Clark
Matt Clark was an American character actor known for his numerous supporting roles in Westerns and other films and television series from the 1960s onward.
-
C.
Matthew Clark
Matthew Clark is a cinematographer known for his work on the comedy film "Mike and Dave Need Wedding Dates."
-
D.
Daryl Hicks
Daryl Hicks is a notable individual recognized for achievements significant enough to be distinguished among people sharing the surname Hicks.
-
E.
Chris Clemons
Chris Clemons is an American professional basketball player known for his prolific scoring ability as an undersized guard, particularly during his standout college career at Campbell University and subsequent time in the NBA.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6a1b648190a8bb2deb67bbdfdc |
completed | April 19, 2026, 1:22 a.m. |
Created at: April 10, 2026, 5:39 a.m.