Triple
T15986927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | To My Dear and Loving Husband |
E387719
|
entity |
| Predicate | expressionOf |
P4750
|
FINISHED |
| Object | female voice in early American poetry |
—
|
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: female voice in early American poetry | Statement: [To My Dear and Loving Husband, expressionOf, female voice in early American poetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expressionOf Context triple: [To My Dear and Loving Husband, expressionOf, female voice in early American poetry]
-
A.
expression
Indicates that one entity is a linguistic, mathematical, or symbolic representation or manifestation of another entity.
-
B.
expresses
chosen
Indicates that one entity conveys, communicates, or articulates a thought, feeling, or idea through another medium or form.
-
C.
expressivePower
Indicates the degree to which one system, language, or formalism can represent or capture the behaviors, structures, or concepts expressible in another.
-
D.
oftenExpressedAs
Indicates that one thing is frequently represented, stated, or manifested in the form of another.
-
E.
expressiveQuality
Indicates the distinctive emotional or stylistic character conveyed by something, such as how it feels, sounds, or appears in an expressive sense.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4e871c819082d7b1c1eaf5b4fe |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.