Triple
T9370927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hound of the Baskervilles |
E225526
|
entity |
| Predicate | workInSherlockHolmesCanon |
P88195
|
FINISHED |
| Object | third novel |
—
|
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: third novel | Statement: [The Hound of the Baskervilles, workInSherlockHolmesCanon, third novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workInSherlockHolmesCanon Context triple: [The Hound of the Baskervilles, workInSherlockHolmesCanon, third novel]
-
A.
numberInHolmesNovels
Indicates that a given number is the count of occurrences or instances of something within the set of Holmes novels.
-
B.
roleInSherlock
Indicates the specific role or character that an entity portrays or holds in the context of the Sherlock series or franchise.
-
C.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
D.
fictionalDetective
Indicates that the subject is a detective character who exists only in fiction rather than in real life.
-
E.
notableInvestigator
Indicates that one entity is a distinguished or prominently recognized investigator or researcher associated with another entity.
- 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_69ca842cbddc819099d71ecec48cf9e5 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5083cbb8819088e8cef26be1b380 |
completed | April 1, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69cc7a6abb8c81908c7a2f4ee92cc949 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:43 p.m.