Triple
T14687958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Never Dies |
E344962
|
entity |
| Predicate | prequelOrSequel |
P92686
|
FINISHED |
| Object | sequel |
—
|
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: sequel | Statement: [Love Never Dies, prequelOrSequel, sequel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prequelOrSequel Context triple: [Love Never Dies, prequelOrSequel, sequel]
-
A.
prequelOrSequelTo
chosen
Indicates that one work in a narrative series occurs earlier or later in the storyline or release order relative to another work, as its prequel or sequel.
-
B.
isPrequelTo
Indicates that one work or event occurs earlier in time and narratively sets up or leads into another work or event.
-
C.
hasSequelDepiction
Indicates that one depiction of something is followed by another depiction that continues its story or sequence.
-
D.
hasSequel
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
E.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb58306548190b981956a83a84b95 |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.