Triple
T10974580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don John |
E259334
|
entity |
| Predicate | relationshipToDon Pedro |
P96934
|
FINISHED |
| Object | illegitimate brother |
—
|
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: illegitimate brother | Statement: [Don John, relationshipToDon Pedro, illegitimate brother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToDon Pedro Context triple: [Don John, relationshipToDon Pedro, illegitimate brother]
-
A.
relationshipToSanchoPanza
Indicates the specific type of relationship or connection an entity has to Sancho Panza.
-
B.
relationshipToPrincess
Indicates the specific familial, social, or romantic connection that one entity has to a princess.
-
C.
relationshipTypeWith Queen Anne of Austria
Indicates the specific nature or category of relational connection an entity has with Queen Anne of Austria (e.g., familial, political, or social relationship).
-
D.
relationToDominicanFamily
Indicates a familial or kinship relationship that a person has with a Dominican family.
-
E.
relationshipToPierreBezukhov
Indicates the specific type of personal or social relationship an entity has to Pierre Bezukhov.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f3794c8190b1992b4695139b62 |
completed | April 9, 2026, 9:31 a.m. |
| PD | Predicate disambiguation | batch_69d72e8c27cc81908050590b7a04cafd |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.