Triple
T4342046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Experimental Advanced Superconducting Tokamak |
E97804
|
entity |
| Predicate | heatingMethod |
P56153
|
FINISHED |
| Object | neutral beam injection |
—
|
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: neutral beam injection | Statement: [Experimental Advanced Superconducting Tokamak, heatingMethod, neutral beam injection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heatingMethod Context triple: [Experimental Advanced Superconducting Tokamak, heatingMethod, neutral beam injection]
-
A.
hasHeating
Indicates that an entity is equipped with or provides a heating system or heating capability.
-
B.
boilerType
Indicates the specific kind or category of boiler associated with an entity, such as its design, fuel source, or operating characteristics.
-
C.
temperatureControlMethod
Indicates the method or mechanism used to regulate or maintain a desired temperature.
-
D.
heatTransferMethod
Indicates the mechanism or process by which heat is transferred from one entity or system to another.
-
E.
coolingMethod
Indicates the technique or process used to remove heat from something or keep it at a lower temperature.
- 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351878c148190b384053479d41caf |
completed | March 12, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b350d1649881908fa6556d875a8b4d |
completed | March 12, 2026, 11:48 p.m. |
Created at: March 12, 2026, 11:14 p.m.