Triple
T17906993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Wilson |
E447726
|
entity |
| Predicate | characterTypeVoiced |
P129249
|
FINISHED |
| Object | elderly farmer |
—
|
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: elderly farmer | Statement: [Lionel Wilson, characterTypeVoiced, elderly farmer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterTypeVoiced Context triple: [Lionel Wilson, characterTypeVoiced, elderly farmer]
-
A.
hasVoiceActing
Indicates that one entity provides voice performance for a character, role, or work associated with another entity.
-
B.
notableCharacterVoiced
Indicates that a notable character is voiced or performed by a specific voice actor or performer.
-
C.
voiceActingType
Indicates the specific style or category of voice performance used in an audio-visual work or production.
-
D.
spokenBy
Indicates that a particular utterance, statement, or piece of speech is produced or said by a specific entity.
-
E.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9d458881909e35e1c7a6e85436 |
completed | April 19, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
| PDg | Predicate description generation | batch_69e3db77df0c819084548168c62b398c |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:19 a.m.