Triple
T2512611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Lansing |
E52734
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object |
Taku City
Taku City is a municipality in Saga Prefecture, Japan, known for its historic sites and traditional Japanese townscape.
|
E285606
|
NE FINISHED |
How this triple was built (4 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: Taku City | Statement: [East Lansing, hasSisterCity, Taku City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taku City Context triple: [East Lansing, hasSisterCity, Taku City]
-
A.
Tomakomai
Tomakomai is an industrial port city on the southern coast of Hokkaido, Japan, known for its paper manufacturing, shipping, and ferry connections.
-
B.
Kushiro
Kushiro is a coastal city in eastern Hokkaido, Japan, known for its large fishing port, cool maritime climate, and nearby wetlands rich in wildlife such as red-crowned cranes.
-
C.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
D.
Daikanyama
Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
-
E.
Yufuin
Yufuin is a scenic hot spring resort town in Ōita Prefecture, Japan, known for its tranquil rural atmosphere, boutique inns, and views of Mount Yufu.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Taku City Triple: [East Lansing, hasSisterCity, Taku City]
Generated description
Taku City is a municipality in Saga Prefecture, Japan, known for its historic sites and traditional Japanese townscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taku City Target entity description: Taku City is a municipality in Saga Prefecture, Japan, known for its historic sites and traditional Japanese townscape.
-
A.
Tomakomai
Tomakomai is an industrial port city on the southern coast of Hokkaido, Japan, known for its paper manufacturing, shipping, and ferry connections.
-
B.
Kushiro
Kushiro is a coastal city in eastern Hokkaido, Japan, known for its large fishing port, cool maritime climate, and nearby wetlands rich in wildlife such as red-crowned cranes.
-
C.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
D.
Daikanyama
Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
-
E.
Yufuin
Yufuin is a scenic hot spring resort town in Ōita Prefecture, Japan, known for its tranquil rural atmosphere, boutique inns, and views of Mount Yufu.
- F. None of above. chosen
Provenance (5 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1efb5c48190a9b47b39a388412b |
completed | March 7, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98a8887c8190bd00eaf48bc77781 |
completed | March 10, 2026, 4:06 a.m. |
| NEDg | Description generation | batch_69af99e3e4bc819080ac8a379592c6d2 |
completed | March 10, 2026, 4:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af9a3716e08190a559684dbc7df774 |
completed | March 10, 2026, 4:12 a.m. |
Created at: March 6, 2026, 9:46 p.m.