Triple
T37359301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deh vieni, non tardar |
E927535
|
entity |
| Predicate | operaCharacterAffiliation |
P203914
|
FINISHED |
| Object | servant of the Countess Almaviva |
—
|
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: servant of the Countess Almaviva | Statement: [Deh vieni, non tardar, operaCharacterAffiliation, servant of the Countess Almaviva]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operaCharacterAffiliation Context triple: [Deh vieni, non tardar, operaCharacterAffiliation, servant of the Countess Almaviva]
-
A.
operaCharacterName
Indicates that the subject is the name (or names) of a character appearing in an opera.
-
B.
operaCharacterBasedOn
Indicates that an opera character is modeled after, inspired by, or derived from a particular real or fictional person or character.
-
C.
operaActRole
Indicates the role or character that a performer portrays in a specific act of an opera.
-
D.
characterAffiliationPortrayed
Indicates that a portrayal shows a character as being affiliated with a particular group, organization, or side.
-
E.
playerCharacterAffiliation
Indicates the group, faction, or organization with which a player-controlled character is associated or aligned.
- 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_69f76eb701788190b40824bc4594d985 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a02efcb13248190a0bef09ba7869ada |
completed | May 12, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_6a024995e1d081908783ca294d1397c3 |
completed | May 11, 2026, 9:26 p.m. |
| PDg | Predicate description generation | batch_6a02efca70c48190b724c2a76a09cbfb |
completed | May 12, 2026, 9:15 a.m. |
Created at: May 3, 2026, 4:16 p.m.