Triple
T20074557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omega laser system |
E499825
|
entity |
| Predicate | targetChamberType |
P76754
|
FINISHED |
| Object | spherical target chamber |
—
|
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: spherical target chamber | Statement: [Omega laser system, targetChamberType, spherical target chamber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetChamberType Context triple: [Omega laser system, targetChamberType, spherical target chamber]
-
A.
hasChamber
Indicates that one entity possesses, contains, or is associated with a distinct enclosed space or compartment (a chamber).
-
B.
hasChamberStructure
Indicates that an entity possesses a specific internal chamber or compartmentalized structural organization.
-
C.
hasChamberSize
Indicates a relationship where an entity is associated with, or characterized by, a specific size of a chamber or internal compartment.
-
D.
appliesToChamber
Indicates that something is relevant or specifically associated with a particular chamber (such as a room, legislative body, or compartment).
-
E.
typeOfChamber
chosen
Indicates the specific kind or category of chamber that an entity belongs to or is classified as.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66439efe881909a068c3f05022421 |
completed | April 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:40 p.m.