Triple
T16036078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beginning Place |
E388971
|
entity |
| Predicate | hasNoDirectSequels |
P121689
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Beginning Place, hasNoDirectSequels, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoDirectSequels Context triple: [The Beginning Place, hasNoDirectSequels, true]
-
A.
hasSequel
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
B.
hasUnofficialSequels
Indicates that a work is followed by one or more subsequent works that continue its story or concept without being officially recognized as canonical sequels.
-
C.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
-
D.
hasSequelDepiction
Indicates that one depiction of something is followed by another depiction that continues its story or sequence.
-
E.
hasSequelInCanon
Indicates that a work has a subsequent work that continues its story within the officially recognized continuity.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1826f34c081908005bb736f1c485d |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 4:56 a.m.