Triple
T9256380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Memoirs of Sherlock Holmes |
E222452
|
entity |
| Predicate | featuresDetectiveMethod |
P32043
|
FINISHED |
| Object | deductive reasoning |
—
|
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: deductive reasoning | Statement: [The Memoirs of Sherlock Holmes, featuresDetectiveMethod, deductive reasoning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDetectiveMethod Context triple: [The Memoirs of Sherlock Holmes, featuresDetectiveMethod, deductive reasoning]
-
A.
featuresDetectiveDuo
Indicates that the subject involves or centers around a pair of detectives working together as a team.
-
B.
detectiveType
Indicates that one entity is classified as a particular type or category of detective in relation to another entity.
-
C.
featuresMurderInvestigation
Indicates that the subject involves or includes a murder investigation as a central element or storyline.
-
D.
featuresMethod
chosen
Indicates that an entity includes or provides a particular method as part of its functionality or behavior.
-
E.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
- 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b4e2048190af0d65b904677c36 |
completed | April 1, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4e79e48190b3200247f4624867 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:32 p.m.