Triple
T1483968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Look-and-say sequence |
E29421
|
entity |
| Predicate | hasMathematicalArea |
P7033
|
FINISHED |
| Object | combinatorics |
—
|
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: combinatorics | Statement: [Look-and-say sequence, hasMathematicalArea, combinatorics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMathematicalArea Context triple: [Look-and-say sequence, hasMathematicalArea, combinatorics]
-
A.
mathematicalSubjectClassification
chosen
Indicates that one entity classifies the mathematical subject area or field to which another entity (such as a work, concept, or topic) belongs.
-
B.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
C.
mathematicallyUses
Indicates that one entity employs or applies another entity within a mathematical context, such as in a formula, proof, computation, or theoretical framework.
-
D.
associatedMatha
Indicates a relationship where one entity is linked or affiliated with a particular matha (monastic or religious institution).
-
E.
mathematicallyFormulatedBy
Indicates that something (such as a concept, model, or theory) is expressed or defined using mathematical formulations created by a particular agent.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c679714c8190ac53630fb49e19c5 |
completed | March 1, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69a4c486eacc81909c272f9bdf50a7c3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.