Triple
T666910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Article III (National Treatment on Internal Taxation and Regulation) |
E12883
|
entity |
| Predicate | authenticLanguage |
P4185
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Article III (National Treatment on Internal Taxation and Regulation), authenticLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authenticLanguage Context triple: [Article III (National Treatment on Internal Taxation and Regulation), authenticLanguage, English]
-
A.
identityLanguage
Indicates that two language entities are identical or represent the same language.
-
B.
isLanguageOf
chosen
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).
-
C.
recognizedLanguage
Indicates that an entity has identified, detected, or acknowledged a particular language as being used or present.
-
D.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
E.
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.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49ff7ca788190bef58ce46849b9d0 |
completed | March 1, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69a49d18942c819083b3d1887e505900 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.