Triple
T29529754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count Almaviva (Il barbiere di Siviglia) |
E749164
|
entity |
| Predicate | relationshipToRosina |
P203274
|
FINISHED |
| Object | eventual husband |
—
|
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: eventual husband | Statement: [Count Almaviva (Il barbiere di Siviglia), relationshipToRosina, eventual husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToRosina Context triple: [Count Almaviva (Il barbiere di Siviglia), relationshipToRosina, eventual husband]
-
A.
relationshipToHortensio
Indicates the specific type of personal or social connection that one entity has with Hortensio.
-
B.
relationshipToFlorentinoAriza
Indicates the nature of the relationship an entity has with Florentino Ariza.
-
C.
relationshipToLucentio
Indicates the specific type of relationship or connection that an entity has to Lucentio.
-
D.
relationshipToHarpagon
Indicates the specific familial or social relationship that an entity has to the character Harpagon.
-
E.
relationshipToJackWorthing
Indicates the type of personal or social relationship an entity has with Jack Worthing.
- 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_69f0bd46d99c81908ba9d01cc1dbef7d |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_6a01487b73488190954eb5143e6f246e |
completed | May 11, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_6a0145210ae481908da59b02efdbc397 |
completed | May 11, 2026, 2:55 a.m. |
| PDg | Predicate description generation | batch_6a01487ac3608190946beee970e5559b |
completed | May 11, 2026, 3:09 a.m. |
Created at: April 28, 2026, 4:51 p.m.