Triple
T14991479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LBNE experiment |
E373843
|
entity |
| Predicate | scienceCase |
P116263
|
FINISHED |
| Object | study of matter–antimatter asymmetry via neutrinos |
—
|
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: study of matter–antimatter asymmetry via neutrinos | Statement: [LBNE experiment, scienceCase, study of matter–antimatter asymmetry via neutrinos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scienceCase Context triple: [LBNE experiment, scienceCase, study of matter–antimatter asymmetry via neutrinos]
-
A.
scienceCaseIncludes
Indicates that a science case encompasses, contains, or makes use of a particular element, component, or resource as part of its scope or definition.
-
B.
scienceDomain
Indicates that one entity is a field, branch, or domain within science to which the other entity is related or belongs.
-
C.
scientificTrackExample
Indicates an example instance or case that illustrates a particular scientific track, pathway, or line of research.
-
D.
investigatesCase
Indicates that one entity conducts an investigation into a particular case involving events, issues, or individuals.
-
E.
scienceReturn
Indicates that an action or process yields scientific data, findings, or value as its outcome.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded715db408190b44e8a8452c79764 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:53 a.m.