Triple
T14901693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jadis et naguère |
E360019
|
entity |
| Predicate | authorStylePeriod |
P18647
|
FINISHED |
| Object | mature style of Paul Verlaine |
—
|
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: mature style of Paul Verlaine | Statement: [Jadis et naguère, authorStylePeriod, mature style of Paul Verlaine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorStylePeriod Context triple: [Jadis et naguère, authorStylePeriod, mature style of Paul Verlaine]
-
A.
authorStyle
Indicates the stylistic characteristics or manner of expression associated with a particular author in their works.
-
B.
followedByPeriod
Indicates that one event, state, or item is immediately succeeded in time or sequence by a subsequent period.
-
C.
stylePeriod
chosen
Indicates the stylistic or historical period with which an entity (such as an artwork, artifact, or performance) is associated.
-
D.
punctuation
Indicates the presence, type, or pattern of punctuation marks used within or between textual elements.
-
E.
abbreviationStyle
Indicates the specific way in which something is abbreviated, such as the format, punctuation, or capitalization used in its shortened form.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded609bf68819099ca3aa3fe1acadc |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:11 a.m.