Triple
T10516642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bildungsroman |
E248051
|
entity |
| Predicate | oftenBeginsWith |
P12097
|
FINISHED |
| Object | youthful innocence |
—
|
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: youthful innocence | Statement: [Bildungsroman, oftenBeginsWith, youthful innocence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenBeginsWith Context triple: [Bildungsroman, oftenBeginsWith, youthful innocence]
-
A.
beganWith
chosen
Indicates that one event, process, or state started with or was initiated by another specified event, process, or state.
-
B.
oftenPrecededBy
Indicates that one event, state, or item commonly occurs or appears before another in time or sequence.
-
C.
oftenAccompaniedBy
Indicates that one entity is frequently found together with, occurs alongside, or is commonly associated in presence or use with another entity.
-
D.
oftenSays
Indicates that one entity frequently makes a particular statement or remark, or regularly expresses a certain idea or phrase.
-
E.
oftenUsedAfter
Indicates that one entity is frequently or typically used immediately following another entity in a sequence or workflow.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509cc58b081908ef15aa89b396db6 |
completed | April 7, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:28 p.m.