Triple
T23988380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrea Rossi |
E604995
|
entity |
| Predicate | technologyTypeClaimed |
P1482
|
FINISHED |
| Object | low-energy nuclear reaction reactor |
—
|
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: low-energy nuclear reaction reactor | Statement: [Andrea Rossi, technologyTypeClaimed, low-energy nuclear reaction reactor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technologyTypeClaimed Context triple: [Andrea Rossi, technologyTypeClaimed, low-energy nuclear reaction reactor]
-
A.
technologyType
chosen
Indicates the specific kind or category of technology associated with an entity or relationship.
-
B.
technologyName
Indicates the specific name or designation of a technology associated with an entity.
-
C.
technologyClass
Indicates the classification or category of technology to which an entity belongs.
-
D.
technologyPresent
Indicates that a particular technology exists, is available, or is currently in use in the given context or situation.
-
E.
technologyUsedBy
Indicates that a particular technology is employed or utilized by a specified entity.
- 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38902fc8190af51cedfce1c6c13 |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:37 p.m.