Triple
T34500801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rogue of the Range |
E885743
|
entity |
| Predicate | characterPlayedByJohnnyMackBrown |
P199960
|
FINISHED |
| Object | Dan Dawson |
—
|
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: Dan Dawson | Statement: [Rogue of the Range, characterPlayedByJohnnyMackBrown, Dan Dawson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedByJohnnyMackBrown Context triple: [Rogue of the Range, characterPlayedByJohnnyMackBrown, Dan Dawson]
-
A.
leadActorForCharacter_MaceBrown
Indicates that a person is the primary actor portraying the character Mace Brown.
-
B.
characterPlayedBy John Hodiak
Indicates that a specific character is portrayed or acted by John Hodiak.
-
C.
leadActorForCharacterJohnnyCarver
Indicates that one entity is the lead actor who portrays the character Johnny Carver in a production.
-
D.
characterPlayedBy Jonathan Tucker
Indicates that the specified character is portrayed or acted by Jonathan Tucker.
-
E.
characterPlayedByEdwardMulhare
Indicates that the subject is a character that was portrayed or played by Edward Mulhare.
- F. None of above. chosen
Provenance (4 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_69f349cc0220819081f154c6964f4dc2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff65987ff88190b09be64f7c0e1da9 |
completed | May 9, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69ff6525b0548190bef7a9f009e00bb8 |
completed | May 9, 2026, 4:47 p.m. |
| PDg | Predicate description generation | batch_69ff659717708190bb56714d1b261063 |
completed | May 9, 2026, 4:49 p.m. |
Created at: May 1, 2026, 2:01 a.m.