Triple
T12652543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 柏原市 |
E302198
|
entity |
| Predicate | 主な駅 |
P30882
|
FINISHED |
| Object |
河内国分駅
河内国分駅は、大阪府柏原市に位置し、近鉄大阪線が乗り入れる同市の主要な鉄道駅です。
|
E996592
|
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: 河内国分駅 | Statement: [柏原市, 主な駅, 河内国分駅]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 河内国分駅 Context triple: [柏原市, 主な駅, 河内国分駅]
-
A.
Chuo-Rinkan Station
Chuo-Rinkan Station is a major railway station in Yamato, Kanagawa Prefecture, Japan, serving as an important suburban transit hub connecting multiple private railway lines to central Tokyo.
-
B.
Nippombashi Station
Nippombashi Station is a major subway and railway hub in Osaka, Japan, serving the bustling Nipponbashi Den Den Town electronics and otaku shopping district.
-
C.
Nijō Station
Nijō Station is a railway and subway station in Kyoto, Japan, serving as an interchange between the Kyoto Municipal Subway Tōzai Line and JR West’s Sagano Line near the historic Nijō Castle.
-
D.
Osaki Station
Osaki Station is a major railway hub in Tokyo, Japan, serving multiple JR East lines and connecting central Tokyo with surrounding suburban areas.
-
E.
Namba Station
Namba Station is one of Osaka’s major railway and subway terminals, serving as a key commercial and transportation hub in the city’s bustling Namba district.
- 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: 河内国分駅 Triple: [柏原市, 主な駅, 河内国分駅]
Generated description
河内国分駅は、大阪府柏原市に位置し、近鉄大阪線が乗り入れる同市の主要な鉄道駅です。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 河内国分駅 Target entity description: 河内国分駅は、大阪府柏原市に位置し、近鉄大阪線が乗り入れる同市の主要な鉄道駅です。
-
A.
Chuo-Rinkan Station
Chuo-Rinkan Station is a major railway station in Yamato, Kanagawa Prefecture, Japan, serving as an important suburban transit hub connecting multiple private railway lines to central Tokyo.
-
B.
Nippombashi Station
Nippombashi Station is a major subway and railway hub in Osaka, Japan, serving the bustling Nipponbashi Den Den Town electronics and otaku shopping district.
-
C.
Nijō Station
Nijō Station is a railway and subway station in Kyoto, Japan, serving as an interchange between the Kyoto Municipal Subway Tōzai Line and JR West’s Sagano Line near the historic Nijō Castle.
-
D.
Osaki Station
Osaki Station is a major railway hub in Tokyo, Japan, serving multiple JR East lines and connecting central Tokyo with surrounding suburban areas.
-
E.
Namba Station
Namba Station is one of Osaka’s major railway and subway terminals, serving as a key commercial and transportation hub in the city’s bustling Namba district.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96411d87481909127e81755f23964 |
completed | April 10, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688104d48190939933b93b7e60cc |
completed | May 2, 2026, 9:11 p.m. |
| NEDg | Description generation | batch_69f66c572f848190a8cad6311d3315a3 |
completed | May 2, 2026, 9:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f66cef79148190a052fb9ade3b0d27 |
completed | May 2, 2026, 9:30 p.m. |
Created at: April 9, 2026, 5:18 p.m.