Triple
T9963569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. ambassador to Belize |
E195624
|
entity |
| Predicate | hasNativeLanguageRequirement |
P66413
|
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: [U.S. ambassador to Belize, hasNativeLanguageRequirement, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNativeLanguageRequirement Context triple: [U.S. ambassador to Belize, hasNativeLanguageRequirement, English]
-
A.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
B.
hasLanguageRestriction
chosen
Indicates that an entity is subject to limitations or specific conditions regarding the languages it can use, support, or be associated with.
-
C.
hasNativeSpeakers
Indicates that a language or dialect is spoken as a first language by one or more people or populations.
-
D.
hasNoNativeSpeakers
Indicates that the language or dialect is not natively acquired as a first language by any living community.
-
E.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
- 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb718cd588190a4aac48220deddec |
completed | April 2, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9ae19c819099fb3635e57c79be |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:47 p.m.