Triple
T36144213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Night Train to Lisbon |
E1045398
|
entity |
| Predicate | titleCharacterInSourceWork |
P161382
|
FINISHED |
| Object | Amadeu de Prado |
—
|
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: Amadeu de Prado | Statement: [Night Train to Lisbon, titleCharacterInSourceWork, Amadeu de Prado]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleCharacterInSourceWork Context triple: [Night Train to Lisbon, titleCharacterInSourceWork, Amadeu de Prado]
-
A.
fictionalCharacterPortrayedFromWorkBy
Indicates that a fictional character is depicted or portrayed in a work that was created by a specific author or creator.
-
B.
characterInBookBy
Indicates that a character appears in a book that was written by a specified author.
-
C.
characterTitle
Indicates that a character holds or is associated with a specific title, rank, or formal designation.
-
D.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
-
E.
workTitleOfCharacter
chosen
Indicates that the specified work (e.g., book, film, game) is the title in which the given character appears.
- 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_69f76e37ace88190a906b107d388f5d1 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff9e91bba08190af04b31ad815b13a |
completed | May 9, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69ff9e00e4808190bde8f07e6519a72c |
completed | May 9, 2026, 8:50 p.m. |
Created at: May 3, 2026, 4:08 p.m.