Triple
T4361375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spenserian stanza |
E98668
|
entity |
| Predicate | hasNinthLineName |
P55775
|
FINISHED |
| Object | alexandrine |
—
|
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: alexandrine | Statement: [Spenserian stanza, hasNinthLineName, alexandrine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNinthLineName Context triple: [Spenserian stanza, hasNinthLineName, alexandrine]
-
A.
lineName
Indicates the specific name or designation assigned to a particular line (such as a route, path, or service) that distinguishes it from other lines.
-
B.
formerLineName
Indicates that the object is a previous or former name by which the referenced line was known.
-
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.
isLinedWith
Indicates that one object or surface is covered, edged, or internally coated along its length or area with another material or layer.
-
E.
hasIconicLine
Indicates that an entity (such as a work or character) is associated with a particularly famous or memorable line of dialogue.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:16 p.m.