Triple
T2734098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orléans |
E60387
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object |
Utsunomiya
Utsunomiya is a city in Tochigi Prefecture, Japan, known as a regional commercial center and for its specialty gyoza (dumplings).
|
E598240
|
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: Utsunomiya | Statement: [Orléans, twinnedWith, Utsunomiya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Utsunomiya Context triple: [Orléans, twinnedWith, Utsunomiya]
-
A.
Omiya
Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
-
B.
Takasaki
Takasaki is a city in Japan’s Gunma Prefecture known for its Daruma doll production and as a regional commercial and transportation hub.
-
C.
Akishima
Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
-
D.
Maebashi
Maebashi is the capital city of Gunma Prefecture in Japan, known as a regional administrative and commercial center on the Kantō Plain.
-
E.
Ibaraki City
Ibaraki City is a suburban city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
- 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: Utsunomiya Triple: [Orléans, twinnedWith, Utsunomiya]
Generated description
Utsunomiya is a city in Tochigi Prefecture, Japan, known as a regional commercial center and for its specialty gyoza (dumplings).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Utsunomiya Target entity description: Utsunomiya is a city in Tochigi Prefecture, Japan, known as a regional commercial center and for its specialty gyoza (dumplings).
-
A.
Omiya
Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
-
B.
Takasaki
Takasaki is a city in Japan’s Gunma Prefecture known for its Daruma doll production and as a regional commercial and transportation hub.
-
C.
Akishima
Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
-
D.
Maebashi
Maebashi is the capital city of Gunma Prefecture in Japan, known as a regional administrative and commercial center on the Kantō Plain.
-
E.
Ibaraki City
Ibaraki City is a suburban city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
- 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c669cd6bb08190966b89a2129f5738 |
completed | March 27, 2026, 11:28 a.m. |
| NEDg | Description generation | batch_69c66c950a908190a42ffcba850a554d |
completed | March 27, 2026, 11:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c66cf75ca08190bb74fec43b63a3f6 |
completed | March 27, 2026, 11:41 a.m. |
Created at: March 6, 2026, 9:56 p.m.