Triple
T36323234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solomon Lane |
E894391
|
entity |
| Predicate | voiceActorInVideoGames |
P185136
|
FINISHED |
| Object | unknown |
—
|
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: unknown | Statement: [Solomon Lane, voiceActorInVideoGames, unknown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voiceActorInVideoGames Context triple: [Solomon Lane, voiceActorInVideoGames, unknown]
-
A.
voiceActorOfPerformer
Indicates that one performer provides the voice for a character or role portrayed by another performer.
-
B.
notableVoiceActor
Indicates that one entity is a voice actor who is especially prominent or well-known for their work on the other entity.
-
C.
voicedByAlsoKnownFor
Indicates that the person who voices a character is also notably recognized for another specific role or work.
-
D.
leadActorAlsoVoices
Indicates that the lead actor in a production also provides the voice for a character, typically in an animated or voice-over role.
-
E.
voiceActorJapanese
Indicates that one entity serves as the Japanese-language voice actor for the other 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_69f76e4d1a788190a6ab6ccca28547a7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb1d6b70819091227bd011734d19 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7ba6c27e081908868a2b50d1d603c |
completed | May 3, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:09 p.m.