Triple
T37831757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinjuku-dori |
E943220
|
entity |
| Predicate | hasSideUse |
P194480
|
FINISHED |
| Object | retail frontage |
—
|
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: retail frontage | Statement: [Shinjuku-dori, hasSideUse, retail frontage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSideUse Context triple: [Shinjuku-dori, hasSideUse, retail frontage]
-
A.
hasByproductUse
Indicates that something produces a secondary material, substance, or outcome that is subsequently used or utilized for another purpose.
-
B.
hasSpecialUse
chosen
Indicates that an entity is used for a particular, non-general or exceptional purpose within a specific context.
-
C.
isSometimesUsedFor
Indicates that something serves a particular purpose or function on some occasions, but not consistently or exclusively.
-
D.
isAlsoUsedAs
Indicates that something serves an additional function or role beyond its primary one.
-
E.
hasSideFeature
Indicates that an entity possesses a specific secondary or auxiliary feature on its side or lateral aspect.
- 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_69f76eea4c8c8190a335aed5955cf2db |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
Created at: May 3, 2026, 4:19 p.m.