Triple
T29531450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selma's Choice |
E749212
|
entity |
| Predicate | hasMainFocusCharacter |
P95658
|
FINISHED |
| Object | Selma Bouvier |
—
|
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: Selma Bouvier | Statement: [Selma's Choice, hasMainFocusCharacter, Selma Bouvier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainFocusCharacter Context triple: [Selma's Choice, hasMainFocusCharacter, Selma Bouvier]
-
A.
hasCharacterFocus
chosen
Indicates that a work, scene, or segment centers primarily on a particular character’s experiences, perspective, or development.
-
B.
hasPrimaryFocus
Indicates that something is the main subject, concern, or area of attention for an entity or activity.
-
C.
hasFocusText
Indicates that one entity provides the primary or highlighted textual content associated with another entity.
-
D.
hasProgramFocus
Indicates that an entity (such as a program or initiative) is oriented around or primarily concerned with a particular thematic area, topic, or objective.
-
E.
hasPrimaryInstrumentFocus
Indicates that an entity’s main emphasis or specialization is centered on a particular instrument.
- 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_69f0bd47abb081909bd6e6a33d770fd8 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69ff56ef0a5c8190ae729d66a8cf7fc4 |
completed | May 9, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ff539859c481909ec56310da418688 |
completed | May 9, 2026, 3:32 p.m. |
Created at: April 28, 2026, 4:53 p.m.