Triple
T1248994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pascal's triangle |
E26830
|
entity |
| Predicate | combinatorialMeaning |
P16024
|
FINISHED |
| Object | C(n,k) counts k-element subsets of an n-element set |
—
|
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: C(n,k) counts k-element subsets of an n-element set | Statement: [Pascal's triangle, combinatorialMeaning, C(n,k) counts k-element subsets of an n-element set]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combinatorialMeaning Context triple: [Pascal's triangle, combinatorialMeaning, C(n,k) counts k-element subsets of an n-element set]
-
A.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
B.
meaningComponent
chosen
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
C.
hasComb
Indicates that an entity possesses or is equipped with a comb.
-
D.
sharesMeaningWith
Indicates that two expressions convey the same or very similar meaning, even if they differ in form or wording.
-
E.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf83b32c81908648e5748b897247 |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6b075881908e867c25b5080e25 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.