Triple
T25658895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bosudong Book Street |
E643320
|
entity |
| Predicate | hasNumberOfBookstores |
P8902
|
FINISHED |
| Object | dozens of bookstores |
—
|
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: dozens of bookstores | Statement: [Bosudong Book Street, hasNumberOfBookstores, dozens of bookstores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfBookstores Context triple: [Bosudong Book Street, hasNumberOfBookstores, dozens of bookstores]
-
A.
numberOfStores
chosen
Indicates the total count of stores associated with a given entity or context.
-
B.
usedAsBookstoreTo
Indicates that one entity functions or is utilized as a bookstore for another entity.
-
C.
hasShopsOn
Indicates that one entity (typically a street, area, or building) contains or is lined with shops located on or along it.
-
D.
hasIndependentShops
Indicates that an entity contains or is associated with retail businesses that operate independently rather than as part of large chains or franchises.
-
E.
hasStoreLocation
Indicates that an entity operates or maintains a store at a specified physical location.
- 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_69e77e7e45648190a068ed3faa8016ea |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 21, 2026, 6:49 p.m.