Triple
T14061196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 7 inside a circle |
E338349
|
entity |
| Predicate | representsLineNumber |
P11728
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [7 inside a circle, representsLineNumber, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsLineNumber Context triple: [7 inside a circle, representsLineNumber, 7]
-
A.
hasLineNumber
chosen
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.
-
B.
lineNumberingIntroduced
Indicates that a system, document, or text has had line numbering initiated or enabled.
-
C.
lineNumbering
Indicates that a specific system or document applies sequential numbers to each line of its content.
-
D.
lineNumberOrCode
Indicates the specific line number or code identifier associated with an element, reference, or occurrence within a structured sequence or document.
-
E.
lineNumberingScheme
Indicates the specific method or convention used to assign and display line numbers within a text or document.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568876308190840361dcaf10bd45 |
completed | April 14, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.