Triple
T23515268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ella of Frell |
E574341
|
entity |
| Predicate | relationshipTypeWithPrinceChar |
P152687
|
FINISHED |
| Object | eventual spouse in the novel's conclusion |
—
|
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 spouse in the novel's conclusion | Statement: [Ella of Frell, relationshipTypeWithPrinceChar, eventual spouse in the novel's conclusion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithPrinceChar Context triple: [Ella of Frell, relationshipTypeWithPrinceChar, eventual spouse in the novel's conclusion]
-
A.
relationshipToPrincess
Indicates the specific familial, social, or romantic connection that one entity has to a princess.
-
B.
relationshipToPrinceDauntless
Indicates the specific familial, social, or interpersonal connection an entity has with Prince Dauntless.
-
C.
relationTypeToHenryVIII
Indicates the specific type of relationship an entity has to Henry VIII (e.g., familial, political, or social connection).
-
D.
characterTypeOfPrince
Indicates that the subject has the character type or role of a prince.
-
E.
royalAssociation
Indicates a relationship in which an entity is connected or linked to royalty, a royal person, or a royal institution.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa80d9048190ab735dddd301feb4 |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:08 p.m.