Triple
T35070566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Double Image |
E1011856
|
entity |
| Predicate | periodOfAuthorLifeReflected |
P161663
|
FINISHED |
| Object | Levertov’s early adulthood |
—
|
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: Levertov’s early adulthood | Statement: [The Double Image, periodOfAuthorLifeReflected, Levertov’s early adulthood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: periodOfAuthorLifeReflected Context triple: [The Double Image, periodOfAuthorLifeReflected, Levertov’s early adulthood]
-
A.
authorLifespanContext
Indicates the temporal or historical context of an author’s life span in relation to other events, periods, or entities.
-
B.
eraOfAuthor
Indicates the historical time period or era during which an author lived or produced their work.
-
C.
workPeriodOfAuthorDescribed
chosen
Indicates that the time period during which an author was active or produced work is being described.
-
D.
activeYearsInLiterature
Indicates the span of years during which an entity was actively producing or contributing to literary works.
-
E.
yearOfAuthorDeathRelation
Indicates the specific year in which the referenced author died.
- 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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.