Triple
T1238242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannah |
E26596
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object |
Anya
Anya is a person known primarily through her relationship to someone named Hannah, likely as a friend or family member.
|
E150553
|
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: Anya | Statement: [Hannah, relatedName, Anya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anya Context triple: [Hannah, relatedName, Anya]
-
A.
Sonya
Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
-
B.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
-
C.
Anastasia Virganskaya
Anastasia Virganskaya is the granddaughter of former Soviet leader Mikhail Gorbachev and the daughter of his only child, Irina Virganskaya.
-
D.
Katya
Katya is a diminutive and affectionate form of the given name Catherine, commonly used in Slavic and other European cultures.
-
E.
Natalia Sedova
Natalia Sedova was a Russian revolutionary, Marxist activist, and intellectual best known as the lifelong partner and political collaborator of Leon Trotsky.
- 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: Anya Triple: [Hannah, relatedName, Anya]
Generated description
Anya is a person known primarily through her relationship to someone named Hannah, likely as a friend or family member.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anya Target entity description: Anya is a person known primarily through her relationship to someone named Hannah, likely as a friend or family member.
-
A.
Sonya
Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
-
B.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
-
C.
Anastasia Virganskaya
Anastasia Virganskaya is the granddaughter of former Soviet leader Mikhail Gorbachev and the daughter of his only child, Irina Virganskaya.
-
D.
Katya
Katya is a diminutive and affectionate form of the given name Catherine, commonly used in Slavic and other European cultures.
-
E.
Natalia Sedova
Natalia Sedova was a Russian revolutionary, Marxist activist, and intellectual best known as the lifelong partner and political collaborator of Leon Trotsky.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf406b988190a12aa26bbcb88d6a |
completed | March 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbadec0808190a3b43e757e1ddeae |
completed | March 7, 2026, 11:55 p.m. |
| NEDg | Description generation | batch_69acbb5ee684819083f5309dc9771c3a |
completed | March 7, 2026, 11:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69acbbfee7e88190b216beef1c862f64 |
completed | March 7, 2026, 11:59 p.m. |
Created at: March 1, 2026, 7:47 p.m.