Triple
T19505660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "The woods are lovely, dark and deep," |
E488014
|
entity |
| Predicate | meterOfSourcePoem |
P82742
|
FINISHED |
| Object | iambic tetrameter |
—
|
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: iambic tetrameter | Statement: ["The woods are lovely, dark and deep,", meterOfSourcePoem, iambic tetrameter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meterOfSourcePoem Context triple: ["The woods are lovely, dark and deep,", meterOfSourcePoem, iambic tetrameter]
-
A.
poemLength
Indicates the length or extent of a poem, typically measured in units such as lines, verses, or words.
-
B.
numberOfStanzasInOriginalPoem
Indicates the total count of stanzas contained in the poem’s original version.
-
C.
writtenInMetre
chosen
Indicates that a piece of writing is composed using a specific metrical pattern or rhythmic structure.
-
D.
poemLengthRange
Indicates the range of acceptable or actual lengths (e.g., in lines, words, or characters) associated with a poem.
-
E.
containsNumberOfPoems
Indicates that one entity includes or specifies a particular quantity of poems associated with it.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635113fdc819098ea0f738d01925c |
completed | April 20, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.