Triple
T14301353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shimo-kitazawa Station |
E354570
|
entity |
| Predicate | connectsToAreaKnownFor |
P113684
|
FINISHED |
| Object | youth culture |
—
|
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: youth culture | Statement: [Shimo-kitazawa Station, connectsToAreaKnownFor, youth culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToAreaKnownFor Context triple: [Shimo-kitazawa Station, connectsToAreaKnownFor, youth culture]
-
A.
connectsArea
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
B.
hasAreaConnections
Indicates that an entity is linked to one or more surrounding or related areas, typically representing spatial or regional connections between them.
-
C.
connectsTypeOfAreas
Indicates a relationship where one entity serves as a link or connector between two different types of areas.
-
D.
connectsToTouristRegion
Indicates that one entity has a direct linkage or association to a tourist region, such as through location, access, or service provision.
-
E.
connectsCentralAreaTo
Indicates a relationship where one element serves as a link or pathway between a central area and another location or component.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717fc2348190bb6ba3109bd2871f |
completed | April 14, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:11 a.m.