Triple
T1129528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar Street |
E24795
|
entity |
| Predicate | hasSequelRelation |
P1961
|
FINISHED |
| Object | concludes the story arc begun in Palace Walk |
—
|
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: concludes the story arc begun in Palace Walk | Statement: [Sugar Street, hasSequelRelation, concludes the story arc begun in Palace Walk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSequelRelation Context triple: [Sugar Street, hasSequelRelation, concludes the story arc begun in Palace Walk]
-
A.
hasSequel
chosen
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
B.
hasSequelNumber
Indicates that an entity is followed by another work in a series identified by a specific sequential number.
-
C.
followsFrom
Indicates that one fact, event, or state logically or causally results from, is implied by, or comes as a consequence of another.
-
D.
hasSubsequentInfluence
Indicates that one entity has an influence or effect that occurs after, and is causally or temporally downstream from, another entity or event.
-
E.
isSuccessorTo
Indicates that one entity directly follows another in an ordered sequence, coming immediately after it.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb48de2081909a0dce005b1c9df1 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.