Triple
T31734800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Set in Darkness |
E809962
|
entity |
| Predicate | hasInspectorRebusNovelSuccessor |
P180120
|
FINISHED |
| Object | The Falls |
—
|
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: The Falls | Statement: [Set in Darkness, hasInspectorRebusNovelSuccessor, The Falls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInspectorRebusNovelSuccessor Context triple: [Set in Darkness, hasInspectorRebusNovelSuccessor, The Falls]
-
A.
hasInspectorRebusNovelPredecessor
Indicates that one Inspector Rebus novel directly precedes another in the series or publication order.
-
B.
hasInspectorRebusNovelNumber
Indicates the specific numbered position of an Inspector Rebus novel within the overall Inspector Rebus series.
-
C.
hasInspectorMorseNovelNumber
Indicates that an entity (a specific work) is associated with a particular numbered position within the Inspector Morse novel series.
-
D.
isSecondNovelBy
Indicates that one entity is the second novel authored by another entity.
-
E.
hasFictionalSuccessor
chosen
Indicates that one entity is followed or replaced by another entity within a fictional or narrative context.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff6a4ce9a08190b98abde3a170dd69 |
completed | May 9, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69ff69c11634819089d1084bd2c11534 |
completed | May 9, 2026, 5:07 p.m. |
Created at: April 30, 2026, 11:23 p.m.