Triple
T723721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XNYS |
E14673
|
entity |
| Predicate | languageOfCode |
P18654
|
FINISHED |
| Object | alphanumeric |
—
|
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: alphanumeric | Statement: [XNYS, languageOfCode, alphanumeric]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCode Context triple: [XNYS, languageOfCode, alphanumeric]
-
A.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
B.
languageName
Indicates the specific name assigned to a language in the relationship.
-
C.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
D.
languageCodeISO639-1
Indicates that the subject entity is associated with the specified two-letter ISO 639-1 language code.
-
E.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5a5360c8190b16e1e4f4206d0aa |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f700cc81908c6de3eedf68433c |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a55a26e081908134ee93faaf7c40 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.