Triple
T22594661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyu Store Chain |
E574641
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Tokyo |
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 | Statement: [Tokyu Store Chain, operatesIn, Tokyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tokyo Context triple: [Tokyu Store Chain, operatesIn, Tokyo]
-
A.
Tokyo
chosen
Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
-
B.
Tokyo
"Tokyo" is a popular Afrobeats song by Ghanaian singer King Promise featuring Nigerian artist Wizkid.
-
C.
Tokyo
Tokyo is a central member of the Professor's heist crew in the Spanish television series "Money Heist" ("La Casa de Papel"), known for her impulsive nature and role as one of the show's primary narrators.
-
D.
Tokio
Tokio is a popular asynchronous runtime for the Rust programming language, providing event-driven, non-blocking I/O for building high-performance network and concurrent applications.
-
E.
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.
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f16164d690819096f7c4efb6cedad9 |
completed | April 29, 2026, 1:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b9e7caad881909ff0c985655f6a75 |
completed | May 18, 2026, 11:19 p.m. |
Created at: April 17, 2026, 2:49 p.m.