Triple
T18158168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SHA-0 |
E434686
|
entity |
| Predicate | roundFunctionCount |
P11575
|
FINISHED |
| Object | 80 rounds |
—
|
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: 80 rounds | Statement: [SHA-0, roundFunctionCount, 80 rounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roundFunctionCount Context triple: [SHA-0, roundFunctionCount, 80 rounds]
-
A.
roundFunctionType
Indicates that a function or operation is of a type that performs a rounding transformation on its input values.
-
B.
usesVariableNumberOfRounds
Indicates that the action or process operates with a variable, rather than fixed, number of rounds or iterations.
-
C.
roundCount
chosen
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
D.
roundOf
Indicates that one event, match, or game occurs as a specific stage or phase within a larger competition or tournament.
-
E.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec02d9c81909ac6203b7d59c405 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.