Triple
T4416494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knuth’s up-arrow notation |
E94986
|
entity |
| Predicate | recurrenceRule |
P25791
|
FINISHED |
| Object | a ↑^n 1 = a for n ≥ 1 |
—
|
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: a ↑^n 1 = a for n ≥ 1 | Statement: [Knuth’s up-arrow notation, recurrenceRule, a ↑^n 1 = a for n ≥ 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurrenceRule Context triple: [Knuth’s up-arrow notation, recurrenceRule, a ↑^n 1 = a for n ≥ 1]
-
A.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
-
B.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
C.
recurringLocation
Indicates that an event, action, or state happens repeatedly at the specified location over time.
-
D.
recurrence
Indicates that an event, condition, or state happens again or repeatedly over time, often after a period of absence or resolution.
-
E.
satisfiesRecurrence
chosen
Indicates that one entity fulfills or conforms to a specified recurrence relation defined by 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551afb448190a2ce2000193808ac |
completed | March 13, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:29 p.m.