Triple
T33699737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Table Manners |
E863420
|
entity |
| Predicate | trilogyDepicts |
P177208
|
FINISHED |
| Object | same weekend from different locations |
—
|
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: same weekend from different locations | Statement: [Table Manners, trilogyDepicts, same weekend from different locations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trilogyDepicts Context triple: [Table Manners, trilogyDepicts, same weekend from different locations]
-
A.
trilogyTheme
Indicates that multiple works in a trilogy share a common overarching theme or central subject.
-
B.
partOfTrilogy
Indicates that one work belongs to a set of three related works that together form a trilogy.
-
C.
filmTrilogyAppearance
Indicates that an entity appears in, or is part of, a specific film trilogy.
-
D.
hasPartInTrilogy
Indicates that an entity is one of the constituent parts (e.g., books, films, or episodes) that together form a specific trilogy.
-
E.
hasTrilogy
Indicates that an entity is part of, or associated with, a specific trilogy within a larger set of works or narratives.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fae2a7a8819099945d1706a94bfd |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f6fa335b908190a20d92d5396203b5 |
completed | May 3, 2026, 7:33 a.m. |
Created at: May 1, 2026, 1:43 a.m.