Triple
T1708956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiga Prefecture |
E36933
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Taga, Shiga
Taga, Shiga is a town in Shiga Prefecture, Japan, known for its historic Taga Taisha shrine and scenic rural surroundings.
|
E206328
|
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: Taga, Shiga | Statement: [Shiga Prefecture, contains, Taga, Shiga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taga, Shiga Context triple: [Shiga Prefecture, contains, Taga, Shiga]
-
A.
Nagaokakyo
Nagaokakyo is a suburban city in Japan known for its bamboo groves, historical temples, and convenient location between Kyoto and Osaka.
-
B.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
-
C.
Moriyama, Shiga
Moriyama, Shiga is a city in central Japan known for its location on the southeastern shore of Lake Biwa and its blend of residential, commercial, and historical areas.
-
D.
Konan, Shiga
Konan, Shiga is a city in Japan known for its rural landscapes, historical temples, and location in the southern part of Shiga Prefecture.
-
E.
Yasu, Shiga
Yasu, Shiga is a city in central Japan known for its location in Shiga Prefecture near Lake Biwa and its blend of residential areas, agriculture, and light industry.
- 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: Taga, Shiga Triple: [Shiga Prefecture, contains, Taga, Shiga]
Generated description
Taga, Shiga is a town in Shiga Prefecture, Japan, known for its historic Taga Taisha shrine and scenic rural surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taga, Shiga Target entity description: Taga, Shiga is a town in Shiga Prefecture, Japan, known for its historic Taga Taisha shrine and scenic rural surroundings.
-
A.
Nagaokakyo
Nagaokakyo is a suburban city in Japan known for its bamboo groves, historical temples, and convenient location between Kyoto and Osaka.
-
B.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
-
C.
Moriyama, Shiga
Moriyama, Shiga is a city in central Japan known for its location on the southeastern shore of Lake Biwa and its blend of residential, commercial, and historical areas.
-
D.
Konan, Shiga
Konan, Shiga is a city in Japan known for its rural landscapes, historical temples, and location in the southern part of Shiga Prefecture.
-
E.
Yasu, Shiga
Yasu, Shiga is a city in central Japan known for its location in Shiga Prefecture near Lake Biwa and its blend of residential areas, agriculture, and light industry.
- 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_69a88617439c819094ffb5d16a0f6307 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa63118618819085700fa84e362d60 |
completed | March 6, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc9974b9c819081e9513ae2a0883b |
completed | March 8, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69adccc396f881908c4e45105a1bfff1 |
completed | March 8, 2026, 7:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adcd3da95081908e676063bf650664 |
completed | March 8, 2026, 7:25 p.m. |
Created at: March 4, 2026, 7:30 p.m.