Triple
T1929801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sendai |
E40916
|
entity |
| Predicate | hasWard |
P14475
|
FINISHED |
| Object |
Taihaku-ku
Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
|
E393894
|
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: Taihaku-ku | Statement: [Sendai, hasWard, Taihaku-ku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taihaku-ku Context triple: [Sendai, hasWard, Taihaku-ku]
-
A.
Jōnan-ku
Jōnan-ku is a residential ward in the city of Fukuoka, Japan, known for its universities, suburban neighborhoods, and access to natural areas.
-
B.
Miyagino-ku
Miyagino-ku is one of the administrative wards of Sendai, Japan, known for its mix of residential areas, commercial facilities, and transportation hubs.
-
C.
Nishi-ku
Nishi-ku is a ward in Fukuoka, Japan, known for its coastal areas, residential neighborhoods, and access to both urban amenities and natural scenery.
-
D.
Nishi-ku
Nishi-ku is a central ward of Yokohama, Japan, known as a major commercial and business district that includes the Minato Mirai 21 waterfront area.
-
E.
Naniwa-ku
Naniwa-ku is a central ward of Osaka, Japan, known for its bustling entertainment districts, shopping streets, and iconic landmarks such as Tsutenkaku Tower.
- 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: Taihaku-ku Triple: [Sendai, hasWard, Taihaku-ku]
Generated description
Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taihaku-ku Target entity description: Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
-
A.
Jōnan-ku
Jōnan-ku is a residential ward in the city of Fukuoka, Japan, known for its universities, suburban neighborhoods, and access to natural areas.
-
B.
Miyagino-ku
Miyagino-ku is one of the administrative wards of Sendai, Japan, known for its mix of residential areas, commercial facilities, and transportation hubs.
-
C.
Nishi-ku
Nishi-ku is a ward in Fukuoka, Japan, known for its coastal areas, residential neighborhoods, and access to both urban amenities and natural scenery.
-
D.
Nishi-ku
Nishi-ku is a central ward of Yokohama, Japan, known as a major commercial and business district that includes the Minato Mirai 21 waterfront area.
-
E.
Naniwa-ku
Naniwa-ku is a central ward of Osaka, Japan, known for its bustling entertainment districts, shopping streets, and iconic landmarks such as Tsutenkaku Tower.
- 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_69a8864711648190b07bed24ed76258e |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb266dcb4819090be83556615d0db |
completed | March 7, 2026, 5:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b503cbee8481908f31124d8bc7fe9c |
completed | March 14, 2026, 6:44 a.m. |
| NEDg | Description generation | batch_69b507f46edc8190b69206a645e0e59c |
completed | March 14, 2026, 7:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b509622e5c8190993d9af5db1cab2a |
completed | March 14, 2026, 7:08 a.m. |
Created at: March 4, 2026, 7:35 p.m.