Triple
T20061005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abuelita Toretto |
E499471
|
entity |
| Predicate | speaksInWork |
P34466
|
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: [Abuelita Toretto, speaksInWork, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: speaksInWork Context triple: [Abuelita Toretto, speaksInWork, English]
-
A.
speaksIn
chosen
Indicates that an entity uses or expresses itself in a particular language or medium when speaking.
-
B.
languageWithinWork
Indicates that a specific language is used or contained within a particular work (such as a document, publication, or creative piece).
-
C.
placeInWork
Indicates that one entity is located or occurs within the spatial or structural context of another entity in a work.
-
D.
primaryLanguageInWork
Indicates that a specified language is the main or predominant language used within a particular work (such as a book, film, or document).
-
E.
givenForWorkIn
Indicates that something (such as payment, benefit, or item) is provided to an entity specifically in exchange for or in connection with work performed in a particular role, job, or context.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6637601dc8190a07fc20844093cb7 |
completed | April 20, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:38 p.m.