Triple
T28332096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le docteur Miracle |
E717561
|
entity |
| Predicate | hasVocalNumberType |
P172813
|
FINISHED |
| Object | aria |
—
|
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: aria | Statement: [Le docteur Miracle, hasVocalNumberType, aria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVocalNumberType Context triple: [Le docteur Miracle, hasVocalNumberType, aria]
-
A.
hasVocalCharacter
Indicates that an entity possesses a particular vocal quality, style, or characteristic in its sound or voice.
-
B.
hasNumberType
Indicates that an entity is associated with a specific category or type of number (such as integer, float, or identifier format).
-
C.
hasPhoneme
Indicates that a linguistic unit (such as a word or morpheme) contains or includes a particular phoneme as part of its sound structure.
-
D.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
-
E.
hasVoiceSystem
Indicates that one entity possesses or is equipped with a particular voice-based system or voice technology.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6b0d21dd08190a9883ff71c94c71c |
completed | May 3, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6afeaaef88190aefa97e83f8db906 |
completed | May 3, 2026, 2:16 a.m. |
Created at: April 28, 2026, 12:33 a.m.