Triple
T8283465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D (vehicle registration code) |
E193734
|
entity |
| Predicate | languageOfLetter |
P38301
|
FINISHED |
| Object | Latin alphabet |
—
|
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: Latin alphabet | Statement: [D (vehicle registration code), languageOfLetter, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLetter Context triple: [D (vehicle registration code), languageOfLetter, Latin alphabet]
-
A.
languageOfLetters
chosen
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
-
B.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
-
C.
languageOfIssue
Indicates the language in which a particular item, document, or resource is issued or published.
-
D.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
E.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7aceec8881909cdfa488dfedc0f5 |
completed | March 31, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69cb70ad9fc081908741f8c4a4141edf |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:52 p.m.