Triple
T1169567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ALS |
E24881
|
entity |
| Predicate | doesNotTypicallyAffect |
P7029
|
FINISHED |
| Object | sensory neurons |
—
|
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: sensory neurons | Statement: [ALS, doesNotTypicallyAffect, sensory neurons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doesNotTypicallyAffect Context triple: [ALS, doesNotTypicallyAffect, sensory neurons]
-
A.
hasNotableImpact
Indicates that one entity exerts a significant or noteworthy influence or effect on another entity or context.
-
B.
doesNotGenerallyApplyTo
chosen
Indicates that a rule, property, or condition is typically not relevant or applicable to the referenced entity or situation in most cases.
-
C.
notTypicallyUsedFor
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
D.
doesNotProtect
Indicates that an entity fails to provide protection or safeguarding to another entity or object.
-
E.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce821b481908bc278a3fa7973f4 |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.