Triple
T1603448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Tower |
E34445
|
entity |
| Predicate | hasSouvenirShops |
P5824
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tokyo Tower, hasSouvenirShops, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSouvenirShops Context triple: [Tokyo Tower, hasSouvenirShops, yes]
-
A.
hasGiftShop
chosen
Indicates that an entity includes or provides access to a gift shop as part of its facilities or services.
-
B.
hasShop
Indicates that one entity owns, operates, or is associated with a shop or retail establishment.
-
C.
hasShoppingMall
Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
-
D.
hasShoppingDistrict
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
-
E.
hasRetailBoutiquesIn
Indicates that an entity operates or maintains retail boutiques located within a specified place or region.
- 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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a95b02cd448190be8e3db9a5a7bac0 |
completed | March 5, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69a907c1cad08190b9728dd557f39aa0 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.