Triple
T22499977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WS 1749 |
E556241
|
entity |
| Predicate | matrixNumberNotation |
P6517
|
FINISHED |
| Object | WS-1749 |
—
|
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: WS-1749 | Statement: [WS 1749, matrixNumberNotation, WS-1749]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matrixNumberNotation Context triple: [WS 1749, matrixNumberNotation, WS-1749]
-
A.
usesPositionalNotation
Indicates that one entity represents numbers using a positional numeral system, where a digit’s value depends on its position.
-
B.
offsetNotation
Indicates that one representation specifies how far and in what way another representation is shifted or displaced from a reference point or baseline.
-
C.
symbolNumber
Indicates a relationship where a specific numerical identifier is assigned to or associated with a particular symbol.
-
D.
typicalNotation
Indicates that one entity is the standard or commonly used symbolic representation (notation) for another entity.
-
E.
notationSystem
chosen
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15cb4ff8c8190af0c60abafefe832 |
completed | April 29, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:50 p.m.