Triple
T25859218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BICEP experiments |
E651435
|
entity |
| Predicate | advantageOfSite |
P67079
|
FINISHED |
| Object | low atmospheric water vapor |
—
|
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 atmospheric water vapor | Statement: [BICEP experiments, advantageOfSite, low atmospheric water vapor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advantageOfSite Context triple: [BICEP experiments, advantageOfSite, low atmospheric water vapor]
-
A.
siteAdvantage
Indicates that one entity benefits from a favorable or superior position, condition, or context relative to another entity.
-
B.
advantageOverApps
Indicates that one entity possesses a benefit or superiority when compared to applications (apps).
-
C.
describesSite
Indicates that one entity provides a description or characterization of a particular site or location.
-
D.
benefitOfLocation
chosen
Indicates that a particular location provides an advantage, positive effect, or beneficial quality to an entity or activity.
-
E.
advantageOverCookies
Indicates a comparative relationship where one option, method, or entity is considered to have benefits or superiority when compared specifically to cookies.
- 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_69e7ab3a199c81909227cb964cacfe24 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6026a80208190a8b1fae20d6ed906 |
completed | May 2, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69f4939148dc81908706cec7d85291bc |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 8:04 a.m.