Triple
T30087599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | lenticulostriate arteries |
E764638
|
entity |
| Predicate | ruptureConsequence |
P168438
|
FINISHED |
| Object | intracerebral hemorrhage |
—
|
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: intracerebral hemorrhage | Statement: [lenticulostriate arteries, ruptureConsequence, intracerebral hemorrhage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruptureConsequence Context triple: [lenticulostriate arteries, ruptureConsequence, intracerebral hemorrhage]
-
A.
consequenceOfCollision
Indicates that one event, state, or condition occurs as a direct result of a collision between entities.
-
B.
consequenceOfDestruction
Indicates that one event, state, or condition occurs as a direct result of a prior act of destruction.
-
C.
consequenceOfExplosion
Indicates that something occurs as a direct result or outcome of an explosion.
-
D.
impactOutcome
Indicates that one entity produces an effect or influence that changes the result, consequence, or final state of another entity or situation.
-
E.
rupturesDuring
Indicates that one event or process ruptures or breaks while another specified event or time period is occurring.
- 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_69f22473c0fc8190a926a8051b3b378b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67d6de8a081909e426dcdf9fe0536 |
completed | May 2, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f6749f205c81909d1aacf462912eee |
completed | May 2, 2026, 10:03 p.m. |
Created at: April 29, 2026, 7:04 p.m.