Triple
T32023945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pound–Rebka experiment |
E817767
|
entity |
| Predicate | usedEffect |
P37149
|
FINISHED |
| Object | Mössbauer effect |
—
|
NE NERFINISHED |
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: Mössbauer effect | Statement: [Pound–Rebka experiment, usedEffect, Mössbauer effect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedEffect Context triple: [Pound–Rebka experiment, usedEffect, Mössbauer effect]
-
A.
usesEffect
Indicates that one entity employs or applies a particular effect to influence or modify another entity or outcome.
-
B.
usesEffectType
chosen
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
-
C.
usedEffectivelyBy
Indicates that something is employed or utilized in a competent, efficient, or successful manner by a particular entity.
-
D.
usedComponent
Indicates that one entity has employed or incorporated another entity as a component in its structure, function, or operation.
-
E.
sideEffect
Indicates that one entity is an unintended or secondary effect resulting from the use or occurrence of another entity.
- 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_69f348fb04e4819081f4eab040ed7959 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b4684000819090d1f2f28af40db9 |
completed | May 3, 2026, 2:35 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:17 a.m.