Triple
T13753745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Chlumsky |
E330420
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Shaun So
Shaun So is an American military veteran and entrepreneur best known as the husband of actress Anna Chlumsky.
|
E1059178
|
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: Shaun So | Statement: [Anna Chlumsky, spouse, Shaun So]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shaun So Context triple: [Anna Chlumsky, spouse, Shaun So]
-
A.
Shaun Frank
Shaun Frank is a Canadian DJ, producer, and songwriter known for his work in electronic dance music and collaborations with prominent artists.
-
B.
Shaun Silva
Shaun Silva is an American music video director known for his extensive work with major country artists and contributions to contemporary country music visuals.
-
C.
Shaun Pye
Shaun Pye is a British comedian, writer, and producer known for his work on television comedies including co-creating the series "There She Goes."
-
D.
Shawn Dou
Shawn Dou is a Chinese-Canadian actor known for his breakout role in Zhang Yimou’s film "Under the Hawthorn Tree" and subsequent performances in both film and television dramas.
-
E.
Shawn Hatosy
Shawn Hatosy is an American actor known for his roles in films like "Alpha Dog" and the TV series "Animal Kingdom."
- 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: Shaun So Triple: [Anna Chlumsky, spouse, Shaun So]
Generated description
Shaun So is an American military veteran and entrepreneur best known as the husband of actress Anna Chlumsky.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shaun So Target entity description: Shaun So is an American military veteran and entrepreneur best known as the husband of actress Anna Chlumsky.
-
A.
Shaun Frank
Shaun Frank is a Canadian DJ, producer, and songwriter known for his work in electronic dance music and collaborations with prominent artists.
-
B.
Shaun Silva
Shaun Silva is an American music video director known for his extensive work with major country artists and contributions to contemporary country music visuals.
-
C.
Shaun Pye
Shaun Pye is a British comedian, writer, and producer known for his work on television comedies including co-creating the series "There She Goes."
-
D.
Shawn Dou
Shawn Dou is a Chinese-Canadian actor known for his breakout role in Zhang Yimou’s film "Under the Hawthorn Tree" and subsequent performances in both film and television dramas.
-
E.
Shawn Hatosy
Shawn Hatosy is an American actor known for his roles in films like "Alpha Dog" and the TV series "Animal Kingdom."
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0215cfa08190aaed8b089aff217b |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a85813e88190a63fecf8b0675df6 |
completed | May 3, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69f7a968c3508190b1a86accb71b34cf |
completed | May 3, 2026, 8 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7aa32b8c8819088bbc9e478c21c06 |
completed | May 3, 2026, 8:04 p.m. |
Created at: April 9, 2026, 10:09 p.m.