Triple
T3530377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinagawa |
E74645
|
entity |
| Predicate | hasMajorArea |
P36071
|
FINISHED |
| Object |
Gotanda
Gotanda is a bustling commercial and entertainment district in Tokyo known for its offices, shopping, and nightlife, located within Shinagawa Ward.
|
E364439
|
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: Gotanda | Statement: [Shinagawa, hasMajorArea, Gotanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gotanda Context triple: [Shinagawa, hasMajorArea, Gotanda]
-
A.
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.
-
B.
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.
-
C.
Nago
Nago is a coastal city in northern Okinawa, Japan, known for its beaches, subtropical climate, and role as a regional commercial and cultural center.
-
D.
Uruma
Uruma is a coastal city in central Okinawa, Japan, known for its scenic islands, historic sites, and U.S. military bases.
-
E.
Etajima
Etajima is a city in Hiroshima Prefecture, Japan, historically known as the site of the Imperial Japanese Naval Academy.
- 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: Gotanda Triple: [Shinagawa, hasMajorArea, Gotanda]
Generated description
Gotanda is a bustling commercial and entertainment district in Tokyo known for its offices, shopping, and nightlife, located within Shinagawa Ward.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gotanda Target entity description: Gotanda is a bustling commercial and entertainment district in Tokyo known for its offices, shopping, and nightlife, located within Shinagawa Ward.
-
A.
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.
-
B.
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.
-
C.
Nago
Nago is a coastal city in northern Okinawa, Japan, known for its beaches, subtropical climate, and role as a regional commercial and cultural center.
-
D.
Uruma
Uruma is a coastal city in central Okinawa, Japan, known for its scenic islands, historic sites, and U.S. military bases.
-
E.
Etajima
Etajima is a city in Hiroshima Prefecture, Japan, historically known as the site of the Imperial Japanese Naval Academy.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc9764a881908aa8d25dc9adf59e |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e97536881908d5ed3dfe602c9e0 |
completed | March 13, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_69b37f232b8881908f7b4df89399d1d8 |
completed | March 13, 2026, 3:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b37f8fea9481909eb82a06e6c71e98 |
completed | March 13, 2026, 3:08 a.m. |
Created at: March 8, 2026, 3:19 p.m.