Triple
T31431139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sexo, pudor y lágrimas |
E801799
|
entity |
| Predicate | boxOfficeSuccessIn |
P11911
|
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: [Sexo, pudor y lágrimas, boxOfficeSuccessIn, Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boxOfficeSuccessIn Context triple: [Sexo, pudor y lágrimas, boxOfficeSuccessIn, Mexico]
-
A.
hasBoxOffice
Indicates that an entity (typically a film or performance) has a specific box office revenue amount or record associated with it.
-
B.
boxOfficeStatus
chosen
Indicates the commercial performance or financial success status of a film or media release at the box office.
-
C.
hasBoxOfficeType
Indicates the classification of a work’s box office performance or revenue category (e.g., type or scale of its box office results).
-
D.
boxOfficeRanking2018
Indicates the position an entity held in box office performance rankings during the year 2018.
-
E.
boxOfficeWorldwideINR
Indicates the total worldwide box office revenue of a work, expressed in Indian Rupees (INR).
- 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_69f348c475348190bf579ca858eec77c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abaa1f648190b77073771df3bf3b |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 8:57 p.m.