Triple
T17449963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLEAR Plus |
E424888
|
entity |
| Predicate | operatedBy |
P86
|
FINISHED |
| Object | CLEAR |
—
|
NE NERFINISHED |
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: CLEAR | Statement: [CLEAR Plus, operatedBy, CLEAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CLEAR Context triple: [CLEAR Plus, operatedBy, CLEAR]
-
A.
Clear
Clear is a central Scientology attainment state in which a person is believed to be free from the influence of the reactive mind and its stored traumas.
-
B.
LEAR
LEAR (Low Energy Antiproton Ring) was a CERN facility designed to store and decelerate antiprotons for precision experiments in antimatter physics.
-
C.
CLEAR Plus
chosen
CLEAR Plus is a paid airport security membership program that uses biometric identity verification to let travelers skip ID checks and access expedited screening lanes at participating airports and venues.
-
D.
CLAR
CLAR is a digital platform designed to streamline and manage research-related administrative and compliance processes.
-
E.
CLARITY
CLARITY is a tissue-clearing technique that renders biological tissues transparent while preserving their molecular and structural integrity for high-resolution imaging and analysis.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4513d00f48190802a3bdc8c8f4db5 |
completed | April 19, 2026, 3:51 a.m. |
Created at: April 10, 2026, 5:47 a.m.