Triple
T1365585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kobe Port Tower |
E29194
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | City of Kobe |
E3089
|
NE 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: City of Kobe | Statement: [Kobe Port Tower, operator, City of Kobe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Kobe Context triple: [Kobe Port Tower, operator, City of Kobe]
-
A.
Kobe
chosen
Kobe is a major port city in Japan’s Kansai region, known for its scenic harbor setting, cosmopolitan atmosphere, and famous Kobe beef.
-
B.
BE KOBE monument
The BE KOBE monument is a popular waterfront landmark and photo spot in Kobe, Japan, symbolizing the city's identity and resilience.
-
C.
Hoop City
Hoop City is a nickname for Springfield, Massachusetts, highlighting its rich basketball history and status as the birthplace of the sport.
-
D.
Chocolate City
Chocolate City is a popular nickname for Washington, D.C., highlighting its historically large and influential African American population and culture.
-
E.
Red City
Red City is a popular nickname for Marrakesh, the historic Moroccan metropolis famed for its reddish sandstone buildings and city walls.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2d1d15481909d58b6fd8aa2e585 |
completed | March 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd47d38388190856b4ae9de1e69d7 |
completed | March 8, 2026, 1:44 a.m. |
Created at: March 1, 2026, 7:57 p.m.