Triple
T7840341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jung-gu, Ulsan |
E181788
|
entity |
| Predicate | belongsToMetropolitanCity |
P294
|
FINISHED |
| Object | Ulsan |
—
|
NE NERFINISHED |
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: Ulsan | Statement: [Jung-gu, Ulsan, belongsToMetropolitanCity, Ulsan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToMetropolitanCity Context triple: [Jung-gu, Ulsan, belongsToMetropolitanCity, Ulsan]
-
A.
metropolitanOf
Indicates that one place serves as the primary metropolitan center or core urban area for another place or region.
-
B.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
C.
includesMajorMetropolitanArea
Indicates that one entity geographically contains or encompasses a major metropolitan area within its boundaries.
-
D.
metropolitanAreaWith
Indicates that one entity is a metropolitan area that includes, is associated with, or encompasses the other entity.
-
E.
partOfMetropolitanArea
chosen
Indicates that one place is included within and belongs to the larger metropolitan area of another place.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb14c589748190b34d0911d373e194 |
completed | March 31, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:47 p.m.