Triple
T28502406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AT-7 (Tyrol) |
E721269
|
entity |
| Predicate | languageCodePrefix |
P195632
|
FINISHED |
| Object | AT |
—
|
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: AT | Statement: [AT-7 (Tyrol), languageCodePrefix, AT]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageCodePrefix Context triple: [AT-7 (Tyrol), languageCodePrefix, AT]
-
A.
languageOfCodePrefix
Indicates that one entity is the programming language associated with, or identified by, the code prefix represented by the other entity.
-
B.
languageCodeMacro
Indicates a relationship where a language is associated with a broader or macro language code that groups it with closely related language varieties.
-
C.
languageCodeStandard
Indicates that a language code conforms to a specific standardized coding scheme (such as ISO language code standards).
-
D.
languageOfCodes
Indicates that a particular language is used for or associated with a given set of codes.
-
E.
languageCodeISO639-1
Indicates that the subject entity is associated with the specified two-letter ISO 639-1 language code.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
| PDg | Predicate description generation | batch_69fddd364c1481908794c9d423bdc2d7 |
completed | May 8, 2026, 12:55 p.m. |
Created at: April 28, 2026, 3:07 a.m.