Triple
T30520946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | conduction aphasia |
E776691
|
entity |
| Predicate | hasTypicalCause |
P708
|
FINISHED |
| Object | ischemic stroke in the dominant hemisphere |
—
|
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: ischemic stroke in the dominant hemisphere | Statement: [conduction aphasia, hasTypicalCause, ischemic stroke in the dominant hemisphere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalCause Context triple: [conduction aphasia, hasTypicalCause, ischemic stroke in the dominant hemisphere]
-
A.
hasTypicalConditions
Indicates that something is associated with conditions or circumstances that are commonly or normally present for it.
-
B.
hasCause
chosen
Indicates that one entity is the reason for, or brings about, the occurrence or existence of another entity or event.
-
C.
hasTypicalSide
Indicates that one entity is the usual or characteristic side (e.g., lateral aspect) associated with another entity.
-
D.
eligibleCause
Indicates that one entity qualifies as a valid or acceptable cause or reason for another entity or outcome.
-
E.
possibleCauseOf
Indicates that one entity is a potential, but not certain, cause or contributing factor to another entity or outcome.
- 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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: April 29, 2026, 8:17 p.m.