Triple
T32641281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zatoichi |
E834484
|
entity |
| Predicate | filmSeriesCount |
P174759
|
FINISHED |
| Object | 26 feature films starring Shintaro Katsu |
—
|
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: 26 feature films starring Shintaro Katsu | Statement: [Zatoichi, filmSeriesCount, 26 feature films starring Shintaro Katsu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmSeriesCount Context triple: [Zatoichi, filmSeriesCount, 26 feature films starring Shintaro Katsu]
-
A.
filmSeries
Indicates that a film is part of, or associated with, a larger film series or franchise.
-
B.
filmSeriesRelation
Indicates a relationship where one film is part of, belongs to, or is connected within a larger film series or franchise.
-
C.
filmSeriesEnd
Indicates that a particular film marks the conclusion or final installment of a film series.
-
D.
filmSeriesStart
Indicates that a particular film marks the beginning or first installment of a film series.
-
E.
filmSeriesChronology
Indicates the chronological ordering relationship between entries within a film series, specifying which films occur earlier or later in the series timeline.
- 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c7e32ec08190b74856937c4a9fc3 |
completed | May 3, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c77500a08190b2bdeca33bd2ac08 |
completed | May 3, 2026, 3:56 a.m. |
Created at: May 1, 2026, 1:07 a.m.