Triple
T4410538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramanujan partition congruences |
E94841
|
entity |
| Predicate | thirdCongruence |
P56106
|
FINISHED |
| Object | p(11k+6) ≡ 0 (mod 11) |
—
|
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: p(11k+6) ≡ 0 (mod 11) | Statement: [Ramanujan partition congruences, thirdCongruence, p(11k+6) ≡ 0 (mod 11)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdCongruence Context triple: [Ramanujan partition congruences, thirdCongruence, p(11k+6) ≡ 0 (mod 11)]
-
A.
thirdConsul
Indicates that an entity holds the position or role of the third consul in a specified governing body or context.
-
B.
thirdSingle
Indicates that an entity is the third single (e.g., third single release) associated with another entity, typically in a sequence such as from an album or artist.
-
C.
thirdWord
Indicates that one entity is the third word in sequence within another entity (such as a text or phrase).
-
D.
thirdPrecept
Indicates refraining from sexual misconduct or inappropriate sexual behavior in accordance with the third moral precept.
-
E.
thirdTier
Indicates that an entity occupies a third level or rank within a hierarchical structure or classification.
- F. None of above. chosen
Provenance (4 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b354e4c58c8190b4190aad3095a1dd |
completed | March 13, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3509997208190933f167f7e20ccfa |
completed | March 12, 2026, 11:47 p.m. |
Created at: March 12, 2026, 11:29 p.m.