Triple
T25508915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Duchess |
E639317
|
entity |
| Predicate | relationshipToAntonio |
P114153
|
FINISHED |
| Object | lover |
—
|
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: lover | Statement: [the Duchess, relationshipToAntonio, lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAntonio Context triple: [the Duchess, relationshipToAntonio, lover]
-
A.
relationshipToAntonioVillalta
chosen
Indicates the nature of the relationship or connection that an entity has to Antonio Villalta.
-
B.
relationshipTypeWith Aureliano Segundo
Indicates the specific nature or category of relational connection that an entity has with Aureliano Segundo.
-
C.
relationshipWithProspero
Indicates that one entity has a specified type of interpersonal or narrative relationship with Prospero.
-
D.
relationshipToCarmen
Indicates the specific type of personal or social relationship an entity has with Carmen.
-
E.
relationshipWithCaliban
Indicates a relationship or connection that an entity has with Caliban, without specifying the type or nature of that relationship.
- 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_69e75dbd09308190b6b5f0afdc12ec6d |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: April 21, 2026, 2:48 p.m.