Triple
T34372579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La vida inútil de Pito Pérez |
E882199
|
entity |
| Predicate | hasLiterarySourceAuthorNationality |
P135469
|
FINISHED |
| Object | Mexican |
—
|
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: Mexican | Statement: [La vida inútil de Pito Pérez, hasLiterarySourceAuthorNationality, Mexican]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiterarySourceAuthorNationality Context triple: [La vida inútil de Pito Pérez, hasLiterarySourceAuthorNationality, Mexican]
-
A.
hasLiteraryOriginAuthorNationality
chosen
Indicates that the nationality of the author from whom a work or concept originates is being specified.
-
B.
authorNationality
Indicates the relationship between an author and the country or nationality with which that author is identified.
-
C.
literaryOriginCountry
Indicates the country from which a literary work or literary tradition originally comes.
-
D.
literarySourceAuthorRealName
Indicates that the real (legal or birth) name of an author is the source of a given literary work or pseudonymous authorship.
-
E.
literarySource
Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
- 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_69f349bf5d7481908dd5da4cbdf74047 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe779248c081909f0ed1a2a0df23db |
completed | May 8, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69fe76eaf6d48190998bc7168749cc42 |
completed | May 8, 2026, 11:51 p.m. |
Created at: May 1, 2026, 1:59 a.m.