Triple
T12582025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homare Sawa |
E300361
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Sawa
Sawa is a Japanese surname most prominently associated with Homare Sawa, a legendary Japanese women’s footballer and World Cup winner.
|
E1154427
|
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: Sawa | Statement: [Homare Sawa, familyName, Sawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sawa Context triple: [Homare Sawa, familyName, Sawa]
-
A.
Sawata
Sawata was a former town in Niigata Prefecture, Japan, that later became part of the city of Sado through municipal merger.
-
B.
Sakae
Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
-
C.
Sakaide
Sakaide is a coastal city in Japan known for its industrial port facilities and its location near the Seto Ohashi Bridge in Kagawa Prefecture on Shikoku Island.
-
D.
Takizawa
Takizawa is a city in northeastern Japan known for its rural landscapes and proximity to the regional center of Morioka in Iwate Prefecture.
-
E.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
- 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: Sawa Triple: [Homare Sawa, familyName, Sawa]
Generated description
Sawa is a Japanese surname most prominently associated with Homare Sawa, a legendary Japanese women’s footballer and World Cup winner.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sawa Target entity description: Sawa is a Japanese surname most prominently associated with Homare Sawa, a legendary Japanese women’s footballer and World Cup winner.
-
A.
Sawata
Sawata was a former town in Niigata Prefecture, Japan, that later became part of the city of Sado through municipal merger.
-
B.
Sakae
Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
-
C.
Sakaide
Sakaide is a coastal city in Japan known for its industrial port facilities and its location near the Seto Ohashi Bridge in Kagawa Prefecture on Shikoku Island.
-
D.
Takizawa
Takizawa is a city in northeastern Japan known for its rural landscapes and proximity to the regional center of Morioka in Iwate Prefecture.
-
E.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954b97a508190b6c901c506441dd0 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1330527481908d518093debc9ad1 |
completed | May 9, 2026, 10:57 a.m. |
| NEDg | Description generation | batch_69ff142e99e081909d01cac0416f1bde |
completed | May 9, 2026, 11:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff14c61eb08190ba854b541eb1ce14 |
completed | May 9, 2026, 11:04 a.m. |
Created at: April 9, 2026, 5:02 p.m.