Triple
T19241813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcaic stanza |
E481150
|
entity |
| Predicate | line3SyllableCount |
P6574
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Alcaic stanza, line3SyllableCount, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: line3SyllableCount Context triple: [Alcaic stanza, line3SyllableCount, 9]
-
A.
hasSyllableCount
chosen
Indicates that one entity (typically a word or phrase) possesses a specific number of syllables given by the other entity.
-
B.
languageOfSyllables
Indicates a relationship where a language is characterized or defined by the specific set or system of syllables it uses.
-
C.
hasTotalSyllableCountPerStanza
Indicates that a stanza is associated with the total number of syllables it contains.
-
D.
usesSyllables
Indicates that one entity forms, expresses, or analyzes something by employing syllables as its basic units.
-
E.
line3OpeningSegment
Indicates that something is the initial or opening segment of a third line in a sequence or structure.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faf2353c819094a9a1af3a858715 |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dcfae6f081909cc173cf71a5005c |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:27 p.m.