Triple
T22695248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokai to Kamioka |
E561156
|
entity |
| Predicate | beamlineType |
P149335
|
FINISHED |
| Object | conventional horn-focused neutrino beamline |
—
|
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: conventional horn-focused neutrino beamline | Statement: [Tokai to Kamioka, beamlineType, conventional horn-focused neutrino beamline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beamlineType Context triple: [Tokai to Kamioka, beamlineType, conventional horn-focused neutrino beamline]
-
A.
beamLine
Indicates a relationship where one entity directs or projects a beam or focused line (such as light, energy, or signal) toward another entity.
-
B.
beamlineMedium
Indicates that one entity serves as the medium or material through which a beamline passes or operates in relation to another entity.
-
C.
hasBeamlines
Indicates that one entity possesses, contains, or is associated with one or more beamlines.
-
D.
beamName
Indicates that an entity has or is associated with a specific beam identifier or label.
-
E.
beamType
Indicates the specific kind or category of beam involved in the relationship or action.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789d46c881908176bc8e26f366f6 |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:14 p.m.