Triple
T1096031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M2 beam line |
E24273
|
entity |
| Predicate | beamUse |
P23064
|
FINISHED |
| Object | fixed-target experiments |
—
|
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: fixed-target experiments | Statement: [M2 beam line, beamUse, fixed-target experiments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beamUse Context triple: [M2 beam line, beamUse, fixed-target experiments]
-
A.
beam
Indicates that one entity emits, directs, or projects a concentrated line or stream (such as light, energy, or information) toward another entity.
-
B.
beamType
Indicates the specific kind or category of beam involved in the relationship or action.
-
C.
usesPrimaryBeam
Indicates that one entity employs another entity as its main or principal beam in an operation or structure.
-
D.
hasTypicalBeam
Indicates that an entity is associated with a characteristic or standard type of beam it commonly uses or possesses.
-
E.
beamLine
Indicates a relationship where one entity directs or projects a beam or focused line (such as light, energy, or signal) toward another entity.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99ffb3481908cd168b6c58e1c6d |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b7448c148190a3c9a4158ebd05b4 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:42 p.m.