Triple
T635927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tennoji Station |
E16620
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Namba area |
E4490
|
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: Namba area | Statement: [Tennoji Station, connectsTo, Namba area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namba area Context triple: [Tennoji Station, connectsTo, Namba area]
-
A.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
B.
Namba
chosen
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
-
C.
Tetsugaku-no-michi area
Tetsugaku-no-michi area is a scenic, cherry tree–lined pedestrian path in Kyoto known for its temples, traditional atmosphere, and association with Japanese philosophers.
-
D.
Kitano-cho
Kitano-cho is a historic district in Kobe, Japan, known for its preserved Western-style residences built by foreign merchants in the late 19th and early 20th centuries.
-
E.
Rioni
The Rioni is a major river in western Georgia that flows through the city of Kutaisi before emptying into the Black Sea.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee667f08190a0332b8f6c569e1a |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56ef25ffc81908517310fe0c84a68 |
completed | March 2, 2026, 11:05 a.m. |
Created at: March 1, 2026, 7:35 p.m.