Triple
T15439685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XXX |
E369864
|
entity |
| Predicate | additiveNotation |
P118795
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [XXX, additiveNotation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: additiveNotation Context triple: [XXX, additiveNotation, true]
-
A.
usesSubtractiveNotation
Indicates that something represents values by subtracting one symbol’s value from another, as in numeral systems where smaller units placed before larger ones denote a difference rather than a sum.
-
B.
usesPositionalNotation
Indicates that one entity represents numbers using a positional numeral system, where a digit’s value depends on its position.
-
C.
offsetNotation
Indicates that one representation specifies how far and in what way another representation is shifted or displaced from a reference point or baseline.
-
D.
usesNumeralsFrom
Indicates that one writing system, notation, or representation employs the numeral symbols originating from another system.
-
E.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03eddf258819082679970b7d2b6af |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:21 a.m.