Triple
T9240460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aeroport |
E222043
|
entity |
| Predicate | nativeNameLanguageCode |
P26955
|
FINISHED |
| Object | ru |
—
|
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: ru | Statement: [Aeroport, nativeNameLanguageCode, ru]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeNameLanguageCode Context triple: [Aeroport, nativeNameLanguageCode, ru]
-
A.
localLanguageName
Indicates the name of a language as it is written or referred to in its own local or native form.
-
B.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
C.
hasLanguageOfOfficialName
chosen
Indicates that an entity’s official name is expressed in a specified language.
-
D.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
E.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
- 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_69ca83ee26cc81909ac624e190597d6d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccf0a3888c8190b72d8d0b850bdfbc |
completed | April 1, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4765648190aa9445c4a22dc471 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:30 p.m.