Triple
T13011586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naniwa-ku, Osaka |
E322427
|
entity |
| Predicate | hasMajorDistrict |
P14817
|
FINISHED |
| Object |
Naniwanishi
Naniwanishi is a major urban district within Osaka's Naniwa Ward, known for its dense cityscape and local commercial activity.
|
E1015451
|
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: Naniwanishi | Statement: [Naniwa-ku, Osaka, hasMajorDistrict, Naniwanishi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naniwanishi Context triple: [Naniwa-ku, Osaka, hasMajorDistrict, Naniwanishi]
-
A.
Nanikai
Nanikai is a locality within South Tarawa, the densely populated capital area of Kiribati in the central Pacific Ocean.
-
B.
Nakoruru
Nakoruru is a popular Samurai Shodown character known as a nature-loving Ainu shrine maiden who fights alongside her hawk and wolf companions.
-
C.
Nabitasan
Nabitasan is a barangay (village-level administrative division) of the municipality of Oton in the province of Iloilo, Philippines.
-
D.
Kudanshita
Kudanshita is a district and major subway station area in central Tokyo known for its proximity to the Imperial Palace, Yasukuni Shrine, and several universities and office buildings.
-
E.
Kulisusu
Kulisusu is a town and administrative center located in the province of Southeast Sulawesi, Indonesia.
- 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: Naniwanishi Triple: [Naniwa-ku, Osaka, hasMajorDistrict, Naniwanishi]
Generated description
Naniwanishi is a major urban district within Osaka's Naniwa Ward, known for its dense cityscape and local commercial activity.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Naniwanishi Target entity description: Naniwanishi is a major urban district within Osaka's Naniwa Ward, known for its dense cityscape and local commercial activity.
-
A.
Nanikai
Nanikai is a locality within South Tarawa, the densely populated capital area of Kiribati in the central Pacific Ocean.
-
B.
Nakoruru
Nakoruru is a popular Samurai Shodown character known as a nature-loving Ainu shrine maiden who fights alongside her hawk and wolf companions.
-
C.
Nabitasan
Nabitasan is a barangay (village-level administrative division) of the municipality of Oton in the province of Iloilo, Philippines.
-
D.
Kudanshita
Kudanshita is a district and major subway station area in central Tokyo known for its proximity to the Imperial Palace, Yasukuni Shrine, and several universities and office buildings.
-
E.
Kulisusu
Kulisusu is a town and administrative center located in the province of Southeast Sulawesi, Indonesia.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9e14b88190a2cee8e0c9bf31c8 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c10d5b9881909db688c1ab0e6a77 |
completed | May 3, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69f6c277e6248190870b3bf9869716a7 |
completed | May 3, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c38bc0b08190b76cb0853d99ad82 |
completed | May 3, 2026, 3:39 a.m. |
Created at: April 9, 2026, 8:49 p.m.