Triple
T1742809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tama |
E38268
|
entity |
| Predicate | containsAdministrativeUnit |
P3892
|
FINISHED |
| Object |
Hinohara
Hinohara is a rural village in western Tokyo, Japan, known for its mountainous terrain, forests, and outdoor recreation areas.
|
E359474
|
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: Hinohara | Statement: [Tama, containsAdministrativeUnit, Hinohara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hinohara Context triple: [Tama, containsAdministrativeUnit, Hinohara]
-
A.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
B.
Higashikurume
Higashikurume is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and role as a commuter area for central Tokyo.
-
C.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
-
D.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
E.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
- 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: Hinohara Triple: [Tama, containsAdministrativeUnit, Hinohara]
Generated description
Hinohara is a rural village in western Tokyo, Japan, known for its mountainous terrain, forests, and outdoor recreation areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hinohara Target entity description: Hinohara is a rural village in western Tokyo, Japan, known for its mountainous terrain, forests, and outdoor recreation areas.
-
A.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
B.
Higashikurume
Higashikurume is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and role as a commuter area for central Tokyo.
-
C.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
-
D.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
E.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abaffd9b68819084f6c4d5e1aace1e |
completed | March 7, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b36067f47881908de481e1350bcaff |
completed | March 13, 2026, 12:55 a.m. |
| NEDg | Description generation | batch_69b3614702348190bd35c37d2059312f |
completed | March 13, 2026, 12:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b362451b848190a2fe80a17ab8f9c3 |
completed | March 13, 2026, 1:03 a.m. |
Created at: March 4, 2026, 7:30 p.m.