Triple
T29200140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Van Hopper |
E740244
|
entity |
| Predicate | relationshipToUnnamedNarrator |
P203032
|
FINISHED |
| Object | employer |
—
|
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: employer | Statement: [Mrs. Van Hopper, relationshipToUnnamedNarrator, employer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToUnnamedNarrator Context triple: [Mrs. Van Hopper, relationshipToUnnamedNarrator, employer]
-
A.
narratorRole
Indicates that one entity serves as the narrator of another entity (such as a story, text, or media work), specifying the narrative role or function it performs.
-
B.
narratorType
Indicates the narrative perspective or role from which a story or account is being told.
-
C.
narratorCharacterName
Indicates that a given character is the one serving as the narrator, and specifies the name used for that narrator.
-
D.
narratorOf
Indicates that one entity serves as the narrator or storytelling voice for another entity, such as a text, story, or media work.
-
E.
narratorBasedOn
Indicates that a narrative’s narrator is modeled on, inspired by, or derived from a particular real or fictional entity.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_6a0117b6539c8190be7d231e891fe546 |
completed | May 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_6a011762f7ec8190afc884b92419d33f |
completed | May 10, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_6a0117b4eec88190a761ac126f5cc8e2 |
completed | May 10, 2026, 11:41 p.m. |
Created at: April 28, 2026, 12:06 p.m.