Triple
T428725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rip Van Winkle |
E9666
|
entity |
| Predicate | protagonistStatusBeforeSleep |
P13812
|
FINISHED |
| Object | colonial subject of King George III |
—
|
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: colonial subject of King George III | Statement: [Rip Van Winkle, protagonistStatusBeforeSleep, colonial subject of King George III]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistStatusBeforeSleep Context triple: [Rip Van Winkle, protagonistStatusBeforeSleep, colonial subject of King George III]
-
A.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
B.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
C.
spokenBefore
Indicates that one entity has spoken or produced speech earlier in time than another entity.
-
D.
turnedPro
Indicates that an individual transitioned from amateur status to professional status in a particular field or activity.
-
E.
preparesFor
Indicates that one entity is used, designed, or undertaken in order to get another entity ready for a future event, state, or activity.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eeecb64c81908c5c83ef7c0181e6 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd7a3608190b8785c7b7205f6c1 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb93584819082f23eff13e17c4f |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.