Triple
T13894173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadamard’s example of ill-posed problems |
E334044
|
entity |
| Predicate | usedToTeach |
P61611
|
FINISHED |
| Object | difference between well-posed and ill-posed problems |
—
|
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: difference between well-posed and ill-posed problems | Statement: [Hadamard’s example of ill-posed problems, usedToTeach, difference between well-posed and ill-posed problems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToTeach Context triple: [Hadamard’s example of ill-posed problems, usedToTeach, difference between well-posed and ill-posed problems]
-
A.
hasTeaching
Indicates that one entity provides instruction or educational guidance to another entity.
-
B.
hasTeachingRole
Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
-
C.
hasTeacher
Indicates that one entity serves as an instructor or educator for another entity.
-
D.
hasTeachingStatus
Indicates that an entity holds a particular teaching-related role, capacity, or status in relation to another entity or context.
-
E.
taughtThat
chosen
Indicates that one entity provided instruction or education to another entity about a specific subject, skill, or concept.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a741908190bdf46d76c5f1411a |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
Created at: April 9, 2026, 10:15 p.m.