Triple
T26249589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Elton |
E656543
|
entity |
| Predicate | misunderstands |
P38994
|
FINISHED |
| Object | Emma Woodhouse’s intentions |
—
|
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: Emma Woodhouse’s intentions | Statement: [Mr. Elton, misunderstands, Emma Woodhouse’s intentions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: misunderstands Context triple: [Mr. Elton, misunderstands, Emma Woodhouse’s intentions]
-
A.
misinterpretedBy
chosen
Indicates that something (such as a statement, action, or signal) is understood incorrectly or in a way not intended by a particular entity.
-
B.
misjudges
Indicates that one entity forms an incorrect or unfair opinion or assessment about another entity or situation.
-
C.
understands
Indicates that one entity comprehends, grasps the meaning of, or correctly interprets information, ideas, or expressions associated with another entity.
-
D.
romanticMisunderstandingsWith
Indicates a situation where two entities experience confusion, misinterpretation, or mistaken beliefs about each other’s romantic feelings, intentions, or relationship status.
-
E.
notableMisconception
Indicates that a commonly held but incorrect belief or understanding exists about the subject.
- 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60dc94bf881908c91f372e8880a0e |
completed | May 2, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 9:06 p.m.