Triple
T1169541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ALS |
E24881
|
entity |
| Predicate | hasIncidence |
P24571
|
FINISHED |
| Object | about 1–2 per 100000 person-years |
—
|
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: about 1–2 per 100000 person-years | Statement: [ALS, hasIncidence, about 1–2 per 100000 person-years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIncidence Context triple: [ALS, hasIncidence, about 1–2 per 100000 person-years]
-
A.
hasNotableIncident
Indicates that an entity is associated with a significant or noteworthy event, occurrence, or incident.
-
B.
hasIndication
Indicates that one entity (typically a product, treatment, or intervention) is intended, approved, or suitable for use in addressing, preventing, or managing a particular condition, purpose, or circumstance.
-
C.
hasCase
Indicates that one entity is involved in, associated with, or characterized by a particular case, instance, or occurrence represented by another entity.
-
D.
occurredIn
Indicates that an event or action took place within a specific location, context, or time frame.
-
E.
hasAct
Indicates that an entity performs, participates in, or is associated with a specific act or action.
- 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_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. |
| PDg | Predicate description generation | batch_69a4bbd7ff1881908c943ecdfea59e81 |
completed | March 1, 2026, 10:21 p.m. |
Created at: March 1, 2026, 7:45 p.m.