Triple
T7376768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Arthur |
E170143
|
entity |
| Predicate | hasSeriousIllness |
P4720
|
FINISHED |
| Object | amyotrophic lateral sclerosis |
—
|
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: amyotrophic lateral sclerosis | Statement: [John Arthur, hasSeriousIllness, amyotrophic lateral sclerosis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeriousIllness Context triple: [John Arthur, hasSeriousIllness, amyotrophic lateral sclerosis]
-
A.
isTerminallyIll
Indicates that an entity is suffering from an incurable illness expected to lead to death in the relatively near future.
-
B.
hasHealthConcern
chosen
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
C.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
D.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
-
E.
hasPossibleSymptom
Indicates that an entity (such as a condition or disease) may be associated with a particular symptom that can potentially occur.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1a8b18c8190ad1a19521eda2319 |
completed | March 27, 2026, 9:07 p.m. |
| PD | Predicate disambiguation | batch_69c6f02ee3e08190a7a00c981129b22c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:07 p.m.