Triple
T715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States of America |
E14
|
entity |
| Predicate | deFactoLanguage |
P237
|
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: [United States of America, deFactoLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deFactoLanguage Context triple: [United States of America, deFactoLanguage, English]
-
A.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
B.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
C.
developed
Indicates that one entity created, designed, or brought another entity into a more advanced or complete state through effort or work.
-
D.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
E.
status
Indicates the current condition, state, or standing of an entity within a given context.
- 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23211f05c8190b8deb03a8540d84d |
completed | Feb. 28, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69a230c2c48481908beb1db3cc9768aa |
completed | Feb. 28, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69a23211181c81909c2db8796d2aded4 |
completed | Feb. 28, 2026, 12:08 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.