Triple
T38139020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voices of Old People |
E952427
|
entity |
| Predicate | featuresVoicesOf |
P207612
|
FINISHED |
| Object | elderly people |
—
|
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 people | Statement: [Voices of Old People, featuresVoicesOf, elderly people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresVoicesOf Context triple: [Voices of Old People, featuresVoicesOf, elderly people]
-
A.
hasVoices
Indicates that an entity possesses or includes one or more vocal parts, voice tracks, or spoken/sung voice elements.
-
B.
hasVoiceActing
Indicates that one entity provides voice performance for a character, role, or work associated with another entity.
-
C.
speakerFeatures
Indicates that certain characteristics, attributes, or properties are associated with a speaker in a given context.
-
D.
voiceCharacter
Indicates that one entity provides the voice for, or vocally portrays, a particular character in a work.
-
E.
voicedByAlsoKnownFor
Indicates that the person who voices a character is also notably recognized for another specific role or work.
- 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_69f76f09a7148190a4b91c0bacdc127a |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037df009f4819082e04683e6e8a106 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:21 p.m.