Triple
T16307802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Synchrotron Radiation Facility |
E395967
|
entity |
| Predicate | numberOfBeamlines |
P52380
|
FINISHED |
| Object | 40+ |
—
|
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: 40+ | Statement: [European Synchrotron Radiation Facility, numberOfBeamlines, 40+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBeamlines Context triple: [European Synchrotron Radiation Facility, numberOfBeamlines, 40+]
-
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.
beamlineMedium
Indicates that one entity serves as the medium or material through which a beamline passes or operates in relation to another entity.
-
D.
numberOfDetectors
Indicates the quantity of detectors associated with or involved in a given entity or system.
-
E.
numberOfLaserBeams
Indicates the quantity of laser beams associated with or produced by an entity in a given context.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288d776808190a7c9918477f07216 |
completed | April 17, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.