Triple
T15588169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DFGP |
E374674
|
entity |
| Predicate | hasAcronymVariantLanguage |
P119331
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [DFGP, hasAcronymVariantLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcronymVariantLanguage Context triple: [DFGP, hasAcronymVariantLanguage, English]
-
A.
hasAcronymExpansionLanguage
Indicates that a specified language is the language in which an acronym’s full expansion is expressed.
-
B.
hasEthnonymVariant
Indicates that one ethnonym is an alternative or variant form of another ethnonym referring to the same ethnic group.
-
C.
labelLanguageVariant
Indicates that one label is a language-specific variant or localized form of another label.
-
D.
hasAcronymOrigin
Indicates that an acronym is derived from or originates from a specific longer expression or name.
-
E.
officialLanguageVariant
Indicates that one language variety is an officially recognized form or version of another language within a specific jurisdiction or 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_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.