Triple
T22842134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OPERA |
E566109
|
entity |
| Predicate | laboratoryType |
P149927
|
FINISHED |
| Object | underground laboratory |
—
|
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: underground laboratory | Statement: [OPERA, laboratoryType, underground laboratory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laboratoryType Context triple: [OPERA, laboratoryType, underground laboratory]
-
A.
laboratoryModule
Indicates a relationship where an entity is a laboratory module or functions as a lab-specific component or unit within a larger system or structure.
-
B.
laboratoryContext
Indicates that an action or relationship occurs within, is associated with, or is conditioned by a laboratory setting or experimental environment.
-
C.
takenInLaboratoryOf
Indicates that something (such as a sample, measurement, or observation) was obtained or performed within a specific laboratory.
-
D.
laboratoryAnalysis
Indicates that a sample or material is being examined, tested, or measured using scientific procedures in a laboratory setting.
-
E.
laboratoryTestType
Indicates the specific kind or category of laboratory test that is performed or ordered in a medical or experimental context.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e855abc8190b9cf8cc515090a7f |
completed | April 29, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:35 p.m.