Triple
T26703447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nippori Fabric Town |
E673221
|
entity |
| Predicate | hasApproximateNumberOfShops |
P8902
|
FINISHED |
| Object | over 80 |
—
|
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: over 80 | Statement: [Nippori Fabric Town, hasApproximateNumberOfShops, over 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfShops Context triple: [Nippori Fabric Town, hasApproximateNumberOfShops, over 80]
-
A.
hasShopsOn
Indicates that one entity (typically a street, area, or building) contains or is lined with shops located on or along it.
-
B.
numberOfStores
chosen
Indicates the total count of stores associated with a given entity or context.
-
C.
hasIndependentShops
Indicates that an entity contains or is associated with retail businesses that operate independently rather than as part of large chains or franchises.
-
D.
hasShop
Indicates that one entity owns, operates, or is associated with a shop or retail establishment.
-
E.
isLargestShopOn
Indicates that a shop is the largest (by a specified measure, such as area, sales, or inventory) among all shops located on a particular street or area.
- 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 27, 2026, 3:32 a.m.