Triple
T31528085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katerina Izmailova |
E804399
|
entity |
| Predicate | operaTitleConnection |
P148498
|
FINISHED |
| Object | Lady Macbeth of Mtsensk |
—
|
NE NERFINISHED |
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: Lady Macbeth of Mtsensk | Statement: [Katerina Izmailova, operaTitleConnection, Lady Macbeth of Mtsensk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operaTitleConnection Context triple: [Katerina Izmailova, operaTitleConnection, Lady Macbeth of Mtsensk]
-
A.
operaTitleCharacter
chosen
Indicates that a character is the title (namesake) character of a given opera.
-
B.
operaAct
Indicates that an entity performs in or takes part in an act (segment) of an opera performance.
-
C.
associatedOpera
Indicates that there is a relationship linking an entity to an opera with which it is connected or related (e.g., as subject, inspiration, or context).
-
D.
numberOfOperas
Indicates the total count of operas associated with a given entity (such as a person, organization, or catalog entry).
-
E.
cataloguedWithOpera
Indicates that an item is recorded or documented in association with a specific opera work or opera-related cataloging system.
- 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_69f348cf839c81908657048402f7f97b |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ffb5c373948190a6606e8caa87a384 |
completed | May 9, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ffb261da788190b41399df8ed895e8 |
completed | May 9, 2026, 10:17 p.m. |
Created at: April 30, 2026, 9:59 p.m.