Triple
T37470544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theotar the Mad Duke |
E931140
|
entity |
| Predicate | voicedInLanguage |
P191407
|
FINISHED |
| Object | English |
—
|
LITERAL 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: English | Statement: [Theotar the Mad Duke, voicedInLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voicedInLanguage Context triple: [Theotar the Mad Duke, voicedInLanguage, English]
-
A.
voicedByAlsoKnownFor
Indicates that the person who voices a character is also notably recognized for another specific role or work.
-
B.
voicedByInLatinAmericanSpanishDub
Indicates that an entity serves as the voice actor for another entity specifically in the Latin American Spanish dubbed version of a work.
-
C.
voicedByInEuropeanSpanishDub
Indicates that one entity serves as the voice actor for another entity specifically in the European Spanish dubbed version of a work.
-
D.
characterTypeVoiced
Indicates that one character serves as the voice actor or vocal performer for another character.
-
E.
hasVoiceActing
Indicates that one entity provides voice performance for a character, role, or work associated with another entity.
- 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_69f76ec2af148190897d101070d7f415 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdf22ab8881908b257f16522920c5 |
completed | May 7, 2026, 6:51 p.m. |
Created at: May 3, 2026, 4:17 p.m.