Triple
T27675149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sturm–Liouville problem |
E697758
|
entity |
| Predicate | hasWeightFunction |
P35293
|
FINISHED |
| Object | w(x) |
—
|
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: w(x) | Statement: [Sturm–Liouville problem, hasWeightFunction, w(x)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWeightFunction Context triple: [Sturm–Liouville problem, hasWeightFunction, w(x)]
-
A.
weightingFunction
chosen
Indicates a function that assigns relative importance or influence (weights) to elements within a set, often to adjust their impact in a calculation or decision process.
-
B.
hasMinimumWeight
Indicates that an entity’s weight meets or exceeds a specified minimum threshold.
-
C.
weightingMethod
Indicates how relative importance or influence is assigned to elements within a set, such as criteria, features, or data points, in a calculation or decision process.
-
D.
hasNumberOfWeightLayers
Indicates the relationship that specifies how many distinct weight layers are present in a given model or structure.
-
E.
hasEnergyFunction
Indicates that an entity is associated with, governed by, or characterized through a specific energy function.
- 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_69ef590d458c81909583290c3cd0478b |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 2:43 p.m.