Triple
T35087158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | States Parties to the Biological Weapons Convention |
E1012606
|
entity |
| Predicate | hasLanguageOfReference |
P30204
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [States Parties to the Biological Weapons Convention, hasLanguageOfReference, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfReference Context triple: [States Parties to the Biological Weapons Convention, hasLanguageOfReference, Arabic]
-
A.
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).
-
B.
hasLanguageRepresentation
chosen
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
-
C.
reflectsLanguage
Indicates that one entity expresses, embodies, or reveals the language or linguistic characteristics associated with another entity.
-
D.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
E.
hasLanguageOfSide
Indicates that an entity uses or is associated with a particular language on a specific side or aspect (e.g., one side of a bilingual object or interface).
- 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_69f76dd432ec8190969bc32acfc152b1 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff76ac40988190a34d858b5472ee2b |
completed | May 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69ff760a90948190a12fcb80e6e3e14b |
completed | May 9, 2026, 5:59 p.m. |
Created at: May 3, 2026, 4:01 p.m.