Triple
T25030761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swiss Light Source |
E626835
|
entity |
| Predicate | hasBeamlinesFor |
P52380
|
FINISHED |
| Object | materials imaging |
—
|
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: materials imaging | Statement: [Swiss Light Source, hasBeamlinesFor, materials imaging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeamlinesFor Context triple: [Swiss Light Source, hasBeamlinesFor, materials imaging]
-
A.
hasBeamlines
chosen
Indicates that one entity possesses, contains, or is associated with one or more beamlines.
-
B.
beamLine
Indicates a relationship where one entity directs or projects a beam or focused line (such as light, energy, or signal) toward another entity.
-
C.
hasBeamSpecies
Indicates a relationship where an object or structure possesses or is associated with a particular type or species of beam.
-
D.
beamlineType
Indicates the specific kind or category of beamline associated with an experimental setup or facility.
-
E.
hasTypicalBeam
Indicates that an entity is associated with a characteristic or standard type of beam it commonly uses or possesses.
- 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_69e2ff2a2c088190be513727ee8bfe78 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 6:07 a.m.