Triple
T21763343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max-E3-LIN-2 |
E537215
|
entity |
| Predicate | approximationClass |
P145849
|
FINISHED |
| Object | APX-hard |
—
|
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: APX-hard | Statement: [Max-E3-LIN-2, approximationClass, APX-hard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximationClass Context triple: [Max-E3-LIN-2, approximationClass, APX-hard]
-
A.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
B.
approximationFamily
Indicates a relationship where one entity serves as an approximation or approximate representation of another within a defined family or set of approximations.
-
C.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
D.
approximateEstimation
Indicates an estimation relationship where one value or assessment is only roughly or closely, but not exactly, equal to another.
-
E.
approximationRegion
Indicates a region or range within which a value, object, or condition is considered an acceptable approximation of a reference or target.
- 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f031a711dc8190a786c9849dc344e8 |
completed | April 28, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69e6d054737081908aa7112975b77475 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 6:51 p.m.