Triple
T15588197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DFGP (Romansh) |
E374675
|
entity |
| Predicate | correspondsToAbbreviationInFrench |
P119333
|
FINISHED |
| Object | DFJP |
—
|
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: DFJP | Statement: [DFGP (Romansh), correspondsToAbbreviationInFrench, DFJP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToAbbreviationInFrench Context triple: [DFGP (Romansh), correspondsToAbbreviationInFrench, DFJP]
-
A.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
B.
hasAbbreviationInPortuguese
Indicates that one entity is used as the Portuguese-language abbreviation or shortened form of another entity.
-
C.
isUsedInAbbreviation
Indicates that one entity functions as a shortened or abbreviated form of another entity.
-
D.
eraAbbreviation
Indicates that one term is the standard shortened or abbreviated form of a named historical or chronological era.
-
E.
isCommonAbbreviation
Indicates that one term is a widely used shortened or abbreviated form of another term.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e4a19708190936118d569f3436d |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda817e9881909b0c66fc9056f7d5 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f05f708190850f1d8782e132b0 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:11 a.m.