Triple
T520112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsubara |
E10795
|
entity |
| Predicate | hasTransportConnectionTo |
P11026
|
FINISHED |
| Object |
Habikino
Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
|
E73678
|
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: Habikino | Statement: [Matsubara, hasTransportConnectionTo, Habikino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Habikino Context triple: [Matsubara, hasTransportConnectionTo, Habikino]
-
A.
Kawki
Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
-
B.
Kitchawan
Kitchawan is a small hamlet within the town of Yorktown in Westchester County, New York, known for its residential character and proximity to natural areas.
-
C.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
D.
Asokoro
Asokoro is an upscale residential and administrative district in Abuja, Nigeria, known for hosting many government institutions, embassies, and high-profile residents.
-
E.
Tenjin
Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
- 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: Habikino Triple: [Matsubara, hasTransportConnectionTo, Habikino]
Generated description
Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Habikino Target entity description: Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
-
A.
Kawki
Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
-
B.
Kitchawan
Kitchawan is a small hamlet within the town of Yorktown in Westchester County, New York, known for its residential character and proximity to natural areas.
-
C.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
D.
Asokoro
Asokoro is an upscale residential and administrative district in Abuja, Nigeria, known for hosting many government institutions, embassies, and high-profile residents.
-
E.
Tenjin
Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f3b7557c8190a29cf1de359ea2ea |
completed | Feb. 28, 2026, 1:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a51035ebc48190b51f2148cb51a20f |
completed | March 2, 2026, 4:21 a.m. |
| NEDg | Description generation | batch_69a511f9da608190b276298b44a0d93e |
completed | March 2, 2026, 4:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5127183548190a9c4dc153456490a |
completed | March 2, 2026, 4:30 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.