Triple
T8631461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sherlock Holmes stories |
E204412
|
entity |
| Predicate | numberOfCanonicalStories |
P25499
|
FINISHED |
| Object | 56 |
—
|
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: 56 | Statement: [Sherlock Holmes stories, numberOfCanonicalStories, 56]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCanonicalStories Context triple: [Sherlock Holmes stories, numberOfCanonicalStories, 56]
-
A.
numberOfStories
Indicates the total count of levels or floors that a structure or building has.
-
B.
talesCount
chosen
Indicates the number of tales associated with or attributed to a given entity.
-
C.
storyNumber
Indicates the numerical identifier assigned to a specific story within a collection, sequence, or dataset.
-
D.
numberOfNarrators
Indicates the quantity of distinct narrators associated with a given work or narrative.
-
E.
hasCanonicalNumberOfArticles
Indicates that an entity is associated with a standard, officially recognized count of articles that define or describe 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:27 p.m.