Triple
T6010166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Compact Linear Collider |
E133810
|
entity |
| Predicate | optimizationCriterion |
P27210
|
FINISHED |
| Object | high luminosity at multi-TeV energies |
—
|
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: high luminosity at multi-TeV energies | Statement: [Compact Linear Collider, optimizationCriterion, high luminosity at multi-TeV energies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: optimizationCriterion Context triple: [Compact Linear Collider, optimizationCriterion, high luminosity at multi-TeV energies]
-
A.
typeOfOptimality
chosen
Indicates that one entity specifies the particular notion or criterion of optimality that characterizes another entity’s optimal status or solution.
-
B.
optimizationType
Indicates the specific strategy or method used to improve performance or efficiency within a given process or system.
-
C.
optimizationTarget
Indicates that one entity is the goal or objective that another entity is trying to improve, optimize, or make more efficient.
-
D.
optimizationSolver
Indicates a relationship where a solver entity is used to compute an optimal solution for a given optimization problem or task.
-
E.
supportsOptimizationAlgorithm
Indicates that one entity is capable of running, integrating, or being compatible with a specified optimization algorithm.
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f4ffa008190a8ef701b82260219 |
completed | March 22, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69c049e4daf4819099bf870dc700e0a2 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:06 p.m.