Triple
T4824331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michiko Shōda |
E107785
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Tokyo, Japan |
E5560
|
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: Tokyo, Japan | Statement: [Michiko Shōda, placeOfBirth, Tokyo, Japan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tokyo, Japan Context triple: [Michiko Shōda, placeOfBirth, Tokyo, Japan]
-
A.
Tokyo
chosen
Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
-
B.
Ōta, Tokyo
Ōta, Tokyo is a large ward in southern Tokyo known for its mix of residential and industrial areas and for hosting Haneda Airport, one of Japan’s major international gateways.
-
C.
Tōkyō-wan
Tōkyō-wan is the Japanese name for Tokyo Bay, a major urban bay on the Pacific coast of Honshu that serves as a key economic and transportation hub for the Greater Tokyo Area.
-
D.
Kōtō, Tokyo, Japan
Kōtō is a special ward in eastern Tokyo known for its waterfront areas, reclaimed land, and a mix of residential neighborhoods, commercial districts, and large-scale facilities.
-
E.
Nerima, Tokyo
Nerima, Tokyo is a residential special ward in northwestern Tokyo known for its suburban character, parks, and role as a hub for anime production studios.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6cac2bd08190b3f7cfe691fed052 |
completed | March 20, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed8f8a8a08190b403b8c3caf20009 |
completed | March 21, 2026, 5:44 p.m. |
Created at: March 20, 2026, 1:24 p.m.