Triple
T29732116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry |
E752354
|
entity |
| Predicate | hasSequelContext |
P1961
|
FINISHED |
| Object | Henry: Portrait of a Serial Killer, Part II |
—
|
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: Henry: Portrait of a Serial Killer, Part II | Statement: [Henry, hasSequelContext, Henry: Portrait of a Serial Killer, Part II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSequelContext Context triple: [Henry, hasSequelContext, Henry: Portrait of a Serial Killer, Part II]
-
A.
hasSequelElement
Indicates that one element is a sequel or subsequent installment to another element in a series or sequence.
-
B.
hasSequelRemakeContext
Indicates that one work serves as a sequel or remake of another, continuing or reinterpreting its narrative or context.
-
C.
hasSequelType
Indicates that one work has a sequel of a specified type or category in relation to another work.
-
D.
hasSubsequent
Indicates that one entity occurs, appears, or is positioned after another in a defined sequence or order.
-
E.
hasSequel
chosen
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
- 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_69f0d62a36a88190bf860f00da433ff8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
Created at: April 28, 2026, 7:43 p.m.