Triple
T29200150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Van Hopper |
E740244
|
entity |
| Predicate | attitudeTowardUnnamedNarrator |
P159371
|
FINISHED |
| Object | condescending |
—
|
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: condescending | Statement: [Mrs. Van Hopper, attitudeTowardUnnamedNarrator, condescending]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attitudeTowardUnnamedNarrator Context triple: [Mrs. Van Hopper, attitudeTowardUnnamedNarrator, condescending]
-
A.
narratorAttitude
Indicates the stance, feelings, or evaluative perspective that the narrator holds toward a subject or event in the narrative.
-
B.
attitudeTowardHumanNature
Indicates an entity’s evaluative stance or belief about the fundamental characteristics and tendencies of human nature.
-
C.
narratorType
Indicates the narrative perspective or role from which a story or account is being told.
-
D.
attitudeTowardOthers
chosen
Indicates the nature or disposition of one entity’s feelings, judgments, or behavioral stance toward other entities.
-
E.
settingOfNarrator
Indicates that a given location or context serves as the narrative setting in which the narrator’s story or perspective takes place.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f676f968d08190a4adba0439b438c9 |
completed | May 2, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 28, 2026, 12:06 p.m.