Triple
T8650102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Air (M2, 2022) |
E205076
|
entity |
| Predicate | speakerSystem |
P70173
|
FINISHED |
| Object | four-speaker sound system |
—
|
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: four-speaker sound system | Statement: [MacBook Air (M2, 2022), speakerSystem, four-speaker sound system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: speakerSystem Context triple: [MacBook Air (M2, 2022), speakerSystem, four-speaker sound system]
-
A.
hasSoundSystem
chosen
Indicates that an entity is equipped with or includes a sound system as one of its features.
-
B.
speakerConfiguration
Indicates how speakers are arranged or assigned within an audio or communication setup.
-
C.
speakerChamber
Indicates the legislative chamber or house in which a given speaker holds or held their official position.
-
D.
soundReproductionMethod
Indicates the method or technique used to reproduce or play back sound.
-
E.
speakerType
Indicates the role or category of a participant in a communicative act (e.g., narrator, quoted speaker, system voice) within a given context.
- F. None of above.
Provenance (3 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4813d0548190b203e594acc38c8f |
completed | March 31, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:29 p.m.