Triple
T12945189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CAMELS rating system |
E309741
|
entity |
| Predicate | originalAcronym |
P42398
|
FINISHED |
| Object | CAMEL |
—
|
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: CAMEL | Statement: [CAMELS rating system, originalAcronym, CAMEL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalAcronym Context triple: [CAMELS rating system, originalAcronym, CAMEL]
-
A.
hasAcronymOrigin
Indicates that an acronym is derived from or originates from a specific longer expression or name.
-
B.
acronymOfNativeName
Indicates that one term is an acronym formed from the native-language version of another name.
-
C.
originalFor
Indicates that one entity serves as the source, basis, or prototype from which another entity is derived, adapted, or created.
-
D.
originalLabel
Indicates the primary or initial label or name originally assigned to an entity before any changes or translations.
-
E.
acronymExpansion
chosen
Indicates that one term is an acronym whose letters stand for the words in another, longer expression.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:43 p.m.