Triple
T14437398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoppy-dori |
E357999
|
entity |
| Predicate | hasNeonSigns |
P114273
|
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: [Hoppy-dori, hasNeonSigns, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeonSigns Context triple: [Hoppy-dori, hasNeonSigns, yes]
-
A.
hasSignageIn
Indicates that appropriate signs or signage for an entity are present or installed within a specified location or area.
-
B.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
C.
hasSignageName
Indicates that an entity has a specific name or label as it appears on its physical signage.
-
D.
hasSignageType
Indicates the specific category or kind of signage associated with an object, location, or entity.
-
E.
hasStreetFurniture
Indicates that a location or area contains installed public fixtures such as benches, lamps, bins, or similar street furniture.
- F. None of above. chosen
Provenance (4 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de914a45ec81909ab8ccf302047d7f |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:18 a.m.