Triple
T8923200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephanus pagination |
E212474
|
entity |
| Predicate | lineNumbers |
P73242
|
FINISHED |
| Object | further subdivisions within each section |
—
|
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: further subdivisions within each section | Statement: [Stephanus pagination, lineNumbers, further subdivisions within each section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineNumbers Context triple: [Stephanus pagination, lineNumbers, further subdivisions within each section]
-
A.
lineNumbering
Indicates that a specific system or document applies sequential numbers to each line of its content.
-
B.
lineNumberingIntroduced
Indicates that a system, document, or text has had line numbering initiated or enabled.
-
C.
lineNumberingScheme
chosen
Indicates the specific method or convention used to assign and display line numbers within a text or document.
-
D.
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.
-
E.
loopLine
Indicates that a line or path forms a closed loop, returning to its starting point without interruption.
- 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6652d63881908821c8735984322a |
completed | April 1, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed0ef3c81908cc69eac852ee12a |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:56 p.m.