Triple
T7115493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OBDA systems |
E165807
|
entity |
| Predicate | typicallyUseLanguage |
P72909
|
FINISHED |
| Object | OWL 2 QL |
—
|
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: OWL 2 QL | Statement: [OBDA systems, typicallyUseLanguage, OWL 2 QL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyUseLanguage Context triple: [OBDA systems, typicallyUseLanguage, OWL 2 QL]
-
A.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
B.
typicalLanguageUse
chosen
Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
-
C.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
D.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
E.
parentLanguage
Indicates that one language is the ancestral or source language from which another language is derived or historically developed.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5f401b881909ef4c2ab1e0750db |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:43 p.m.