Triple
T28776151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Tilney |
E726537
|
entity |
| Predicate | relationshipToCatherineMorland |
P66259
|
FINISHED |
| Object | 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: Husband | Statement: [Henry Tilney, relationshipToCatherineMorland, Husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToCatherineMorland Context triple: [Henry Tilney, relationshipToCatherineMorland, Husband]
-
A.
relationshipToMarianneDashwood
Indicates the specific familial, social, or emotional connection that an entity has to Marianne Dashwood.
-
B.
relationshipToCatherine
chosen
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
-
C.
relationshipToEleanorTilney
Indicates the specific type or nature of a subject’s relationship to Eleanor Tilney.
-
D.
relationshipToCatherineLinton
Indicates the specific familial or social relationship that an entity has to Catherine Linton.
-
E.
relationshipToEmmaWoodhouse
Indicates the specific interpersonal or familial connection that an entity has to Emma Woodhouse.
- 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_6a007338002081908cb6340d65ff86d5 |
completed | May 10, 2026, 11:59 a.m. |
| PD | Predicate disambiguation | batch_6a0072a137ac8190a7debeb28e738e03 |
completed | May 10, 2026, 11:57 a.m. |
Created at: April 28, 2026, 6:17 a.m.