Triple
T7323108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dexter Pratt House |
E168799
|
entity |
| Predicate | linkedToPoemTheme |
P52908
|
FINISHED |
| Object | rural craftsmanship and moral virtue |
—
|
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: rural craftsmanship and moral virtue | Statement: [Dexter Pratt House, linkedToPoemTheme, rural craftsmanship and moral virtue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToPoemTheme Context triple: [Dexter Pratt House, linkedToPoemTheme, rural craftsmanship and moral virtue]
-
A.
associatedWithPoem
chosen
Indicates a relationship in which an entity is connected or linked to a particular poem, such as by authorship, subject, reference, or contextual association.
-
B.
containsPoem
Indicates that one entity includes or holds a poem as part of its contents.
-
C.
literaryThemeInvolvement
Indicates the involvement or presence of a particular literary theme within a work, passage, or character arc.
-
D.
languageOfPoetry
Indicates that a specified language is the language in which a given piece of poetry is written or expressed.
-
E.
usedByPoet
Indicates that something (such as a word, style, device, or object) is employed or utilized by a poet.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0446628819093e96236f1aa4a9b |
completed | March 27, 2026, 9:01 p.m. |
| PD | Predicate disambiguation | batch_69c6e77230048190b2c29ca6b3a65b8e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:03 p.m.