Triple
T9076076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wernicke's aphasia |
E217486
|
entity |
| Predicate | hasNaming |
P87066
|
FINISHED |
| Object | impaired |
—
|
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: impaired | Statement: [Wernicke's aphasia, hasNaming, impaired]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNaming Context triple: [Wernicke's aphasia, hasNaming, impaired]
-
A.
usesNamingSystem
Indicates that one entity adopts or applies a particular naming system or convention to identify or label other entities.
-
B.
hasNamingStoryElement
Indicates that something includes or is associated with a narrative element explaining the origin or reasoning behind its name.
-
C.
hasNameCharacteristic
Indicates that an entity possesses a specific quality or attribute related to its name.
-
D.
hasGivenNameBasis
Indicates that one entity’s given name is derived from, based on, or formed using another entity (such as a name, word, or person) as its basis.
-
E.
namedAs
Indicates that one entity is given, known by, or referred to using the name of another entity.
- 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_69ca83d6c14c8190bc056d927f00a2a2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc95c53274819099b3b3047bfe8cc8 |
completed | April 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:12 p.m.