Triple
T3311322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xidan station |
E69578
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Xidan |
E69578
|
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: Xidan | Statement: [Xidan station, locatedIn, Xidan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xidan Context triple: [Xidan station, locatedIn, Xidan]
-
A.
Ginza
Ginza is a famous upscale shopping, dining, and entertainment district in central Tokyo known for its luxury boutiques, department stores, and vibrant nightlife.
-
B.
Xidan station
chosen
Xidan station is a major interchange stop on the Beijing Subway serving the busy commercial and shopping district of Xidan in central Beijing.
-
C.
Tokyo Center
Tokyo Center is an urban satellite campus of Kansai University located in Tokyo, primarily used for specialized programs, research activities, and academic exchanges.
-
D.
Shibuya Mark City
Shibuya Mark City is a large commercial complex in Tokyo’s Shibuya district, featuring offices, a hotel, and a shopping and dining mall directly connected to Shibuya Station.
-
E.
Shibuya Center-gai
Shibuya Center-gai is a bustling pedestrian shopping and entertainment street in Tokyo’s Shibuya district, known for its dense concentration of fashion boutiques, restaurants, and youth culture.
- 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0ec80508190baa78435b983b7b5 |
completed | March 8, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3f0d52081908bbade5e514f17d1 |
completed | March 12, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:11 p.m.