Triple
T31734799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Set in Darkness |
E809962
|
entity |
| Predicate | hasInspectorRebusNovelPredecessor |
P199979
|
FINISHED |
| Object | Dead Souls |
—
|
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: Dead Souls | Statement: [Set in Darkness, hasInspectorRebusNovelPredecessor, Dead Souls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInspectorRebusNovelPredecessor Context triple: [Set in Darkness, hasInspectorRebusNovelPredecessor, Dead Souls]
-
A.
hasInspectorRebusNovelNumber
Indicates the specific numbered position of an Inspector Rebus novel within the overall Inspector Rebus series.
-
B.
isSecondNovelBy
Indicates that one entity is the second novel authored by another entity.
-
C.
hasInspectorMorseNovelNumber
Indicates that an entity (a specific work) is associated with a particular numbered position within the Inspector Morse novel series.
-
D.
hasNovella
Indicates that one entity possesses, includes, or is associated with a novella as part of its contents or attributes.
-
E.
literaryPredecessor
Indicates that one work of literature precedes and influences another in a historically or artistically significant way.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff691f5ae481908597ce245188d31c |
completed | May 9, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69ff67ceeeb081909fd00cad166c4b6a |
completed | May 9, 2026, 4:58 p.m. |
| PDg | Predicate description generation | batch_69ff691e86d0819099fdb5eca5a95632 |
completed | May 9, 2026, 5:04 p.m. |
Created at: April 30, 2026, 11:23 p.m.