Triple
T12011649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitney sum |
E285917
|
entity |
| Predicate | fiberwiseDescription |
P102650
|
FINISHED |
| Object | (E ⊕ F)_x = E_x ⊕ F_x for each x in B |
—
|
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: (E ⊕ F)_x = E_x ⊕ F_x for each x in B | Statement: [Whitney sum, fiberwiseDescription, (E ⊕ F)_x = E_x ⊕ F_x for each x in B]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fiberwiseDescription Context triple: [Whitney sum, fiberwiseDescription, (E ⊕ F)_x = E_x ⊕ F_x for each x in B]
-
A.
fiberCharacteristic
Indicates a relationship where a specific characteristic or property is attributed to a fiber or fibrous material.
-
B.
fiberType
Indicates the specific kind or classification of fiber that characterizes or composes an entity.
-
C.
fiberContent
Indicates that one entity specifies the amount or presence of dietary fiber contained in another entity.
-
D.
textileFeature
Indicates a characteristic, property, or notable aspect associated with a textile or fabric.
-
E.
typicalFabric
Indicates that something is made from or associated with a fabric material that is standard or characteristic for its type.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d7777481908cd5a001f75e2ee3 |
completed | April 10, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d9038e39f881908c58c19802ba2eb0 |
completed | April 10, 2026, 2:05 p.m. |
Created at: April 8, 2026, 9:46 p.m.