Triple
T20654921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musashi-Koyama |
E507597
|
entity |
| Predicate | hasNearbyArea |
P4647
|
FINISHED |
| Object | Gotanda |
—
|
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: Gotanda | Statement: [Musashi-Koyama, hasNearbyArea, Gotanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gotanda Context triple: [Musashi-Koyama, hasNearbyArea, Gotanda]
-
A.
Gotanda
chosen
Gotanda is a bustling commercial and entertainment district in Tokyo known for its offices, shopping, and nightlife, located within Shinagawa Ward.
-
B.
Moru
Moru is a Central Sudanic language spoken primarily by the Moru people in South Sudan.
-
C.
Uraga
Uraga is a historic Japanese port town at the entrance of Tokyo Bay that served as a key naval and shipbuilding center, especially during the late Edo period.
-
D.
Tōgō Jinja
Tōgō Jinja is a Shinto shrine in Japan dedicated to Admiral Tōgō Heihachirō, a famed naval hero of the Russo-Japanese War.
-
E.
Hatta
Hatta is an Indonesian surname most prominently associated with Mohammad Hatta, the country’s first vice president and a leading figure in the struggle for independence.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2ec90e881909250884483429acf |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:43 a.m.