Triple
T10532286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SHA-256 |
E248473
|
entity |
| Predicate | hasNumberOfRounds |
P11575
|
FINISHED |
| Object | 64 |
—
|
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: 64 | Statement: [SHA-256, hasNumberOfRounds, 64]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfRounds Context triple: [SHA-256, hasNumberOfRounds, 64]
-
A.
hasRoudNumber
Indicates that an entity is associated with or assigned a specific round number within a sequence of rounds or stages.
-
B.
hasRound
Indicates that an entity possesses, includes, or is associated with a particular round (e.g., a round of an event, game, or process).
-
C.
hasProperRounds
Indicates that an entity is associated with rounds that meet specified standards or criteria for being considered proper or valid.
-
D.
roundCount
chosen
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
E.
numberOfTurns
Indicates the total count of discrete turns or rotations involved in an interaction, process, or motion.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a17f23081909f3372e160e21670 |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb9729288190a0149f127acd7ae3 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:30 p.m.