Triple
T11404627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serena |
E270203
|
entity |
| Predicate | workLanguageOfOrigin |
P74798
|
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: [Serena, workLanguageOfOrigin, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLanguageOfOrigin Context triple: [Serena, workLanguageOfOrigin, English]
-
A.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
B.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
C.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
D.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
E.
originalLanguageOfWholeWork
chosen
Indicates that a given language is the primary or original language in which an entire work (such as a book, film, or other complete creation) was first produced or expressed.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014ab46881909fa1d425926c617b |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.