Triple
T15446462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hatanodai Station |
E370034
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Hatanodai |
—
|
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: Hatanodai | Statement: [Hatanodai Station, serves, Hatanodai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hatanodai Context triple: [Hatanodai Station, serves, Hatanodai]
-
A.
Hatanodai
chosen
Hatanodai is a residential neighborhood in Tokyo, Japan, known for its local shopping streets and convenient rail connections.
-
B.
Nakanoshima
Nakanoshima is a small Japanese island associated with Etajima in Hiroshima Prefecture, known for its coastal scenery and role within the local island group.
-
C.
Nakanoshima
Nakanoshima is a central river island and business district in Osaka, Japan, known for its government buildings, cultural institutions, and scenic waterfront parks.
-
D.
Maihama
Maihama is a coastal district of Urayasu in Chiba Prefecture, Japan, best known as the location of the Tokyo Disney Resort.
-
E.
Sodegaura
Sodegaura is a coastal city in Chiba Prefecture, Japan, known for its industrial waterfront, proximity to Tokyo Bay, and role within the Keiyō industrial zone.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ef767b4819099f2c0919a158321 |
completed | April 16, 2026, 1:44 a.m. |
Created at: April 10, 2026, 3:21 a.m.