Triple
T7580654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RA (robust nucleus of the arcopallium) |
E179476
|
entity |
| Predicate | lesionEffect |
P53074
|
FINISHED |
| Object | disruption of learned song production |
—
|
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: disruption of learned song production | Statement: [RA (robust nucleus of the arcopallium), lesionEffect, disruption of learned song production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lesionEffect Context triple: [RA (robust nucleus of the arcopallium), lesionEffect, disruption of learned song production]
-
A.
placeOfEffect
Indicates the location or setting where an action, event, or effect takes place or is realized.
-
B.
involvedPhysicalEffect
Indicates that one entity participates in causing, experiencing, or mediating a physical effect on another entity or the environment.
-
C.
toxinEffect
Indicates the harmful impact or physiological response caused by a toxin on a target entity.
-
D.
eventEffect
chosen
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
E.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
- 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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f97717048190b0ca1a74ed8a817e |
completed | March 27, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e04c2c8190a889d928515d9b8e |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:52 p.m.