Triple
T3921305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermi theory of beta decay |
E88964
|
entity |
| Predicate | interactionRange |
P45893
|
FINISHED |
| Object | short-range |
—
|
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: short-range | Statement: [Fermi theory of beta decay, interactionRange, short-range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interactionRange Context triple: [Fermi theory of beta decay, interactionRange, short-range]
-
A.
tieneAlcance
chosen
Indicates that something possesses or has a certain scope, reach, or range of effect in relation to something else.
-
B.
maximumReach
Indicates the greatest extent, distance, or limit that something can reach or influence within a given context.
-
C.
hasLongerReachThan
Indicates that one entity can extend, influence, or physically reach farther than another entity.
-
D.
operationalRange
Indicates the span of conditions (such as distance, time, or environment) within which a system, device, or process can function effectively and safely.
-
E.
hostRange
Indicates the range or set of different hosts that an organism, agent, or system can successfully inhabit, infect, or interact with.
- 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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.