Triple
T35266858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanda-Jimbocho |
E1018541
|
entity |
| Predicate | hasApproximateNumberOfBookstores |
P8902
|
FINISHED |
| Object | about 150 to 200 |
—
|
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: about 150 to 200 | Statement: [Kanda-Jimbocho, hasApproximateNumberOfBookstores, about 150 to 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfBookstores Context triple: [Kanda-Jimbocho, hasApproximateNumberOfBookstores, about 150 to 200]
-
A.
usedAsBookstoreTo
Indicates that one entity functions or is utilized as a bookstore for another entity.
-
B.
numberOfStores
chosen
Indicates the total count of stores associated with a given entity or context.
-
C.
hasStoreLocation
Indicates that an entity operates or maintains a store at a specified physical location.
-
D.
intendedNumberOfBooks
Indicates the number of books that an agent plans or aims to have, produce, read, or otherwise be associated with, as opposed to the number actually realized.
-
E.
operatedBookstore
Indicates that one entity managed and ran the day-to-day operations of a bookstore owned or controlled by another entity.
- 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_69f76de4be5c8190a51705c07612cac8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fdd92396788190ae1424bc1ae55844 |
completed | May 8, 2026, 12:37 p.m. |
| PD | Predicate disambiguation | batch_69fdd678f40481909a717a2daec83b36 |
completed | May 8, 2026, 12:26 p.m. |
Created at: May 3, 2026, 4:02 p.m.