Triple
T11309692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 高槻市 |
E267804
|
entity |
| Predicate | borderWith |
P224
|
FINISHED |
| Object |
京都府長岡京市
京都府長岡京市は、京都府南西部に位置し、古代に長岡京が置かれた歴史と住宅都市としての性格を併せ持つ市である。
|
E917324
|
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: 京都府長岡京市 | Statement: [高槻市, borderWith, 京都府長岡京市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 京都府長岡京市 Context triple: [高槻市, borderWith, 京都府長岡京市]
-
A.
Nakagyō-ku, Kyoto
Nakagyō-ku, Kyoto is a central ward of Kyoto City known for its historic sites, traditional streetscapes, and role as a cultural and commercial hub.
-
B.
Higashiyama-ku, Kyoto
Higashiyama-ku, Kyoto is a historic ward on Kyoto’s eastern side known for its preserved traditional streets, temples, and cultural landmarks.
-
C.
Kōka, Shiga Prefecture
Kōka, Shiga Prefecture is a rural city in Japan’s Kansai region known for its historic ninja heritage and scenic mountain landscapes.
-
D.
Kita-ku, Kyoto
Kita-ku, Kyoto is a northern ward of Kyoto, Japan, known for its historic temples, traditional neighborhoods, and scenic mountainous surroundings.
-
E.
Nishikyo-ku, Kyoto
Nishikyo-ku, Kyoto is a western ward of Kyoto City known for its mix of residential areas, historical sites, and major educational institutions.
- 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: 京都府長岡京市 Triple: [高槻市, borderWith, 京都府長岡京市]
Generated description
京都府長岡京市は、京都府南西部に位置し、古代に長岡京が置かれた歴史と住宅都市としての性格を併せ持つ市である。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 京都府長岡京市 Target entity description: 京都府長岡京市は、京都府南西部に位置し、古代に長岡京が置かれた歴史と住宅都市としての性格を併せ持つ市である。
-
A.
Nakagyō-ku, Kyoto
Nakagyō-ku, Kyoto is a central ward of Kyoto City known for its historic sites, traditional streetscapes, and role as a cultural and commercial hub.
-
B.
Higashiyama-ku, Kyoto
Higashiyama-ku, Kyoto is a historic ward on Kyoto’s eastern side known for its preserved traditional streets, temples, and cultural landmarks.
-
C.
Kōka, Shiga Prefecture
Kōka, Shiga Prefecture is a rural city in Japan’s Kansai region known for its historic ninja heritage and scenic mountain landscapes.
-
D.
Kita-ku, Kyoto
Kita-ku, Kyoto is a northern ward of Kyoto, Japan, known for its historic temples, traditional neighborhoods, and scenic mountainous surroundings.
-
E.
Nishikyo-ku, Kyoto
Nishikyo-ku, Kyoto is a western ward of Kyoto City known for its mix of residential areas, historical sites, and major educational institutions.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a70022081908bc74185003a3503 |
completed | April 19, 2026, 5:01 p.m. |
| NEDg | Description generation | batch_69e510fb1e288190a7a38fe896d7b91d |
completed | April 19, 2026, 5:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e516d0910481908fee176db0d9229b |
completed | April 19, 2026, 5:54 p.m. |
Created at: April 8, 2026, 9:32 p.m.