Triple
T33478383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Hurst |
E857387
|
entity |
| Predicate | treatsCharacterWithDisdain |
P134548
|
FINISHED |
| Object | Elizabeth Bennet |
—
|
NE NERFINISHED |
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: Elizabeth Bennet | Statement: [Mrs. Hurst, treatsCharacterWithDisdain, Elizabeth Bennet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsCharacterWithDisdain Context triple: [Mrs. Hurst, treatsCharacterWithDisdain, Elizabeth Bennet]
-
A.
describesContemptAs
Indicates that one entity characterizes or portrays another entity or subject in terms of contempt.
-
B.
disrespect
chosen
Indicates a relationship in which one entity shows a lack of respect, regard, or consideration toward another.
-
C.
treatsCharacter
Indicates how one character behaves toward or interacts with another character, especially in terms of care, respect, or mistreatment.
-
D.
dislikes
Indicates that one entity has a negative feeling or aversion toward another entity.
-
E.
derogatesFrom
Indicates that one entity diminishes, belittles, or detracts from the value, reputation, or importance of another entity.
- 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_69f3497472508190b300ebd3fd402367 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: May 1, 2026, 1:38 a.m.