Triple
T12235608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musashi-Urawa Station |
E291582
|
entity |
| Predicate | hasAdjacentUrbanArea |
P80694
|
FINISHED |
| Object | residential neighborhoods |
—
|
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: residential neighborhoods | Statement: [Musashi-Urawa Station, hasAdjacentUrbanArea, residential neighborhoods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacentUrbanArea Context triple: [Musashi-Urawa Station, hasAdjacentUrbanArea, residential neighborhoods]
-
A.
hasUrbanAreaApprox
Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
-
B.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
-
C.
hasNearbyCityArea
chosen
Indicates that one area is geographically close to or adjacent to a city area.
-
D.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
-
E.
isUrbanParkAdjacent
Indicates that an urban park is directly next to or shares a boundary with another specified area or feature.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.