Triple
T6430090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sutton's law |
E128156
|
entity |
| Predicate | practicalEffect |
P23809
|
FINISHED |
| Object | streamlines diagnostic workup |
—
|
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: streamlines diagnostic workup | Statement: [Sutton's law, practicalEffect, streamlines diagnostic workup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: practicalEffect Context triple: [Sutton's law, practicalEffect, streamlines diagnostic workup]
-
A.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
B.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for another entity.
-
C.
tookEffect
Indicates that a change, rule, condition, or event became active, operative, or started producing its intended consequences.
-
D.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
E.
notableEffect
chosen
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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06923b12081908a09543450b88c24 |
completed | March 22, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69c060f780b08190aa650b4d1fc51f21 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:44 p.m.