Triple
T15682245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Winger |
E377605
|
entity |
| Predicate | hasLoveInterest |
P7325
|
FINISHED |
| Object |
MP Stella Hansen
MP Stella Hansen is a fictional British Member of Parliament who serves as the romantic interest of John Winger in the work where they appear.
|
E1170781
|
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: MP Stella Hansen | Statement: [John Winger, hasLoveInterest, MP Stella Hansen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MP Stella Hansen Context triple: [John Winger, hasLoveInterest, MP Stella Hansen]
-
A.
Jane Hansen
Jane Hansen is known as the wife of legendary American composer and songwriter Burt Bacharach.
-
B.
Beth Johanssen
Beth Johanssen is a brilliant young NASA systems operator and communications specialist who is part of the Ares 3 crew in Andy Weir’s science fiction novel "The Martian."
-
C.
Annette Stroyberg
Annette Stroyberg was a Danish actress and model best known for her roles in European films of the late 1950s and 1960s.
-
D.
Lisa Mordente
Lisa Mordente is an American actress, singer, dancer, and choreographer known for her work on Broadway and in film and television.
-
E.
Maya Hansen
Maya Hansen is a brilliant botanist and geneticist in the Marvel Cinematic Universe whose Extremis research plays a pivotal role in the events of Iron Man 3.
- 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: MP Stella Hansen Triple: [John Winger, hasLoveInterest, MP Stella Hansen]
Generated description
MP Stella Hansen is a fictional British Member of Parliament who serves as the romantic interest of John Winger in the work where they appear.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MP Stella Hansen Target entity description: MP Stella Hansen is a fictional British Member of Parliament who serves as the romantic interest of John Winger in the work where they appear.
-
A.
Jane Hansen
Jane Hansen is known as the wife of legendary American composer and songwriter Burt Bacharach.
-
B.
Beth Johanssen
Beth Johanssen is a brilliant young NASA systems operator and communications specialist who is part of the Ares 3 crew in Andy Weir’s science fiction novel "The Martian."
-
C.
Annette Stroyberg
Annette Stroyberg was a Danish actress and model best known for her roles in European films of the late 1950s and 1960s.
-
D.
Lisa Mordente
Lisa Mordente is an American actress, singer, dancer, and choreographer known for her work on Broadway and in film and television.
-
E.
Maya Hansen
Maya Hansen is a brilliant botanist and geneticist in the Marvel Cinematic Universe whose Extremis research plays a pivotal role in the events of Iron Man 3.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f306a1c8190a819541a3cc51f5a |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ee4c8688190ae2fefb56171161a |
completed | May 9, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69ff705476008190b6151491bf89654e |
completed | May 9, 2026, 5:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff70ea739081909f63657c8fd6fa81 |
completed | May 9, 2026, 5:37 p.m. |
Created at: April 10, 2026, 4:16 a.m.