Triple
T11319265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sister Agnes |
E268047
|
entity |
| Predicate | settingOfCharacterArc |
P90820
|
FINISHED |
| Object | Catholic convent in Quebec |
—
|
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: Catholic convent in Quebec | Statement: [Sister Agnes, settingOfCharacterArc, Catholic convent in Quebec]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfCharacterArc Context triple: [Sister Agnes, settingOfCharacterArc, Catholic convent in Quebec]
-
A.
characterArcElement
Indicates that one element is a component or stage within a character’s overall developmental arc or transformation.
-
B.
characterArc
Indicates the developmental journey or transformation a character undergoes over the course of a narrative.
-
C.
characterSetting
chosen
Indicates that a character is associated with, appears in, or is situated within a particular setting or environment.
-
D.
plotCharacter
Indicates a relationship where a character plays a role or participates in the narrative plot of a story or work.
-
E.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9de875481908acfa56015d4b46f |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787ad575081908274280bf75d95fd |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.