Triple
T2614572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umeda Sky Building |
E58856
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Umeda district |
E85815
|
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: Umeda district | Statement: [Umeda Sky Building, locatedIn, Umeda district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umeda district Context triple: [Umeda Sky Building, locatedIn, Umeda district]
-
A.
Umeda district
chosen
Umeda district is a major commercial and transportation hub in Osaka, Japan, known for its skyscrapers, shopping complexes, and extensive train and subway connections.
-
B.
Nihombashi district
Nihombashi district is a historic commercial and financial center of Tokyo known for its traditional merchants, department stores, and role as a major business hub.
-
C.
Abeno district
Abeno district is a major commercial and residential area in Osaka, Japan, known for its large shopping complexes and the landmark Abeno Harukas skyscraper.
-
D.
Shinsaibashi
Shinsaibashi is a major shopping and entertainment district in central Osaka, Japan, known for its covered arcade, fashion boutiques, and vibrant nightlife.
-
E.
Nankai District
Nankai District is a central urban district of Tianjin, China, known for its educational institutions, historical sites, and commercial areas.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd87fb87c819093b02c67c76d51fd |
completed | March 7, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b402a702a081909319ba32990fa010 |
completed | March 13, 2026, 12:27 p.m. |
Created at: March 6, 2026, 9:50 p.m.