Triple
T30996836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leticia "La Valkiria" |
E789824
|
entity |
| Predicate | featuredInCountryOfOriginFilm |
P202053
|
FINISHED |
| Object | Mexico |
—
|
NE NERFINISHED |
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: Mexico | Statement: [Leticia "La Valkiria", featuredInCountryOfOriginFilm, Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredInCountryOfOriginFilm Context triple: [Leticia "La Valkiria", featuredInCountryOfOriginFilm, Mexico]
-
A.
featuredInFilmBy
Indicates that an entity is prominently included or showcased within a film that is created, directed, or produced by a specified person or organization.
-
B.
basedInFilm
Indicates that something (such as a character, event, or work) is situated, set, or primarily located within the context or universe of a particular film.
-
C.
featuredInDirector
Indicates that an entity appears as a featured element within a director’s work, such as a film, show, or other directed production.
-
D.
endedInCountry
Indicates that an event, process, or entity’s existence or occurrence concluded within the boundaries of a specified country.
-
E.
visitedInFilm
Indicates that a location or place is depicted as being visited by a character within the events of a film.
- 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a004a8892c08190bcacb952ad737716 |
completed | May 10, 2026, 9:06 a.m. |
| PD | Predicate disambiguation | batch_6a004a44b4948190be4b3dbfce8da020 |
completed | May 10, 2026, 9:05 a.m. |
| PDg | Predicate description generation | batch_6a004a87bb908190a2bd164a60245f1d |
completed | May 10, 2026, 9:06 a.m. |
Created at: April 29, 2026, 8:56 p.m.