Triple
T23884434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Count |
E600289
|
entity |
| Predicate | representsNumbersWith |
P125167
|
FINISHED |
| Object | dots and bars |
—
|
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: dots and bars | Statement: [Long Count, representsNumbersWith, dots and bars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsNumbersWith Context triple: [Long Count, representsNumbersWith, dots and bars]
-
A.
representsDigitsOf
Indicates that one entity encodes or corresponds to the individual digits that make up the numeric value of another entity.
-
B.
usesNumeralsFrom
Indicates that one writing system, notation, or representation employs the numeral symbols originating from another system.
-
C.
numericPartRepresents
Indicates that a numeric component of something stands for or encodes a specific value, property, or aspect of that thing.
-
D.
hasUseInNumerals
chosen
Indicates that something is employed or functions as a component within numeral systems or numerical representations.
-
E.
usesPositionalNotation
Indicates that one entity represents numbers using a positional numeral system, where a digit’s value depends on its position.
- 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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ccfbbe4c819093e590709719ab72 |
completed | April 29, 2026, 9:18 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:24 p.m.