Triple
T3861897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Terrace at Vernonnet |
E90155
|
entity |
| Predicate | artistLifespan |
P27074
|
FINISHED |
| Object | 1867–1947 |
—
|
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: 1867–1947 | Statement: [The Terrace at Vernonnet, artistLifespan, 1867–1947]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artistLifespan Context triple: [The Terrace at Vernonnet, artistLifespan, 1867–1947]
-
A.
creatorLifespan
chosen
Indicates the time period between the birth and death of the creator associated with an entity.
-
B.
authorLifespanContext
Indicates the temporal or historical context of an author’s life span in relation to other events, periods, or entities.
-
C.
authorBirthYear
Indicates the year in which the author of a work or text was born.
-
D.
publicationStatusDuringArtistLife
Indicates whether the work was published while the artist was still alive or only posthumously.
-
E.
timeInArtistCareer
Indicates the point or period within an artist’s professional career at which a given event, work, or activity occurs.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec22a5dc8190be8298d1ce8ca449 |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.