Triple
T10718567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twice |
E252751
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Sana
Sana is a Japanese singer and dancer best known as a member of the South Korean girl group Twice.
|
E881962
|
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: Sana | Statement: [Twice, hasMember, Sana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sana Context triple: [Twice, hasMember, Sana]
-
A.
Sana
Sana is a character in Naguib Mahfouz’s novel "The Thief and the Dogs," playing a role in the protagonist’s turbulent, psychologically driven narrative.
-
B.
Sanae
Sanae is a Japanese feminine given name borne by various notable figures in politics, entertainment, and other fields.
-
C.
Sanja-sama
Sanja-sama is the popular name for Asakusa Shrine, a historic Shinto shrine in Tokyo renowned for its connection to Sensō-ji Temple and the famous Sanja Matsuri festival.
-
D.
Sanaig
Sanaig is a core single malt Scotch whisky expression from Islay’s Kilchoman distillery, known for its balance of bourbon and sherry cask influence with a characteristically smoky, coastal profile.
-
E.
Hana
Hana is a common female given name of Hebrew origin, often associated with meanings like "grace" or "favor."
- F. None of above.
- 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: Sana Triple: [Twice, hasMember, Sana]
Generated description
Sana is a Japanese singer and dancer best known as a member of the South Korean girl group Twice.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sana Target entity description: Sana is a Japanese singer and dancer best known as a member of the South Korean girl group Twice.
-
A.
Sana
Sana is a character in Naguib Mahfouz’s novel "The Thief and the Dogs," playing a role in the protagonist’s turbulent, psychologically driven narrative.
-
B.
Sanae
Sanae is a Japanese feminine given name borne by various notable figures in politics, entertainment, and other fields.
-
C.
Sanja-sama
Sanja-sama is the popular name for Asakusa Shrine, a historic Shinto shrine in Tokyo renowned for its connection to Sensō-ji Temple and the famous Sanja Matsuri festival.
-
D.
Sanaig
Sanaig is a core single malt Scotch whisky expression from Islay’s Kilchoman distillery, known for its balance of bourbon and sherry cask influence with a characteristically smoky, coastal profile.
-
E.
Hana
Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6ff36558c81908682adbe7b5dce05 |
completed | April 9, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbb71dd6f88190beb99ca75914fb09 |
completed | April 12, 2026, 3:15 p.m. |
| NEDg | Description generation | batch_69dbbbe3d9dc819088f85d41ef66ab29 |
completed | April 12, 2026, 3:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dbc58a5ef481908e67fff6686fb506 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 8, 2026, 9:13 p.m.