Triple
T4361387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spenserian stanza |
E98668
|
entity |
| Predicate | hasLineCountPattern |
P4876
|
FINISHED |
| Object | eight pentameter lines plus one hexameter line |
—
|
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: eight pentameter lines plus one hexameter line | Statement: [Spenserian stanza, hasLineCountPattern, eight pentameter lines plus one hexameter line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLineCountPattern Context triple: [Spenserian stanza, hasLineCountPattern, eight pentameter lines plus one hexameter line]
-
A.
hasNumberOfLines
chosen
Indicates the relationship that specifies how many lines are associated with a given entity.
-
B.
hasLineLength
Indicates that one entity has, is characterized by, or is associated with a specific line length value.
-
C.
hasLineNumber
Indicates that something is associated with a specific line number, typically denoting its position within an ordered sequence such as lines of text or code.
-
D.
hasLineGroup
Indicates that one entity is associated with, or belongs to, a particular group or collection of lines.
-
E.
containsLine
Indicates that one entity includes or encloses a specific line within its spatial or structural extent.
- 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351e47d388190b31500189577cd75 |
completed | March 12, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69b34f53e3cc8190bf5d4dbe2413bf65 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:16 p.m.