Triple
T37842123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Reef |
E943506
|
entity |
| Predicate | breakFrequency |
P85
|
FINISHED |
| Object | most frequently breaking section of Banzai Pipeline |
—
|
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: most frequently breaking section of Banzai Pipeline | Statement: [First Reef, breakFrequency, most frequently breaking section of Banzai Pipeline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: breakFrequency Context triple: [First Reef, breakFrequency, most frequently breaking section of Banzai Pipeline]
-
A.
frequency
chosen
Indicates how often an event, action, or relationship occurs within a given period or context.
-
B.
breakType
Indicates the specific kind or category of break or interruption that occurs in a process, activity, or sequence.
-
C.
frequencyChange
Indicates a change in how often an event, action, or state occurs over time.
-
D.
break
Indicates that one entity causes another entity to separate into pieces, stop functioning, or otherwise lose its normal integrity or continuity.
-
E.
breaksWith
Indicates that one entity ends or disrupts an existing association, agreement, or alignment with 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.