Triple
T17522813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Altschuler |
E426716
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Katherine Green
Katherine Green is known as the spouse of American television writer and producer John Altschuler.
|
E1327204
|
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: Katherine Green | Statement: [John Altschuler, spouse, Katherine Green]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katherine Green Context triple: [John Altschuler, spouse, Katherine Green]
-
A.
Katherine Green
Katherine Green is a film editor known for her work on the romantic comedy "40 Days and 40 Nights."
-
B.
Katherine East
Katherine East is a residential suburb of the town of Katherine in Australia's Northern Territory, located within the Big Rivers Region.
-
C.
Katherine Warren
Katherine Warren was an American character actress known for her supporting roles in mid-20th-century films and television.
-
D.
Katherine Scruse
Katherine Scruse is better known as Katherine Jackson, the matriarch of the Jackson family and mother of pop icon Michael Jackson.
-
E.
Katharine Blake
Katharine Blake was a British actress known for her work in mid-20th-century film and television, often portraying strong, dramatic characters.
- 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: Katherine Green Triple: [John Altschuler, spouse, Katherine Green]
Generated description
Katherine Green is known as the spouse of American television writer and producer John Altschuler.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Katherine Green Target entity description: Katherine Green is known as the spouse of American television writer and producer John Altschuler.
-
A.
Katherine Green
Katherine Green is a film editor known for her work on the romantic comedy "40 Days and 40 Nights."
-
B.
Katherine East
Katherine East is a residential suburb of the town of Katherine in Australia's Northern Territory, located within the Big Rivers Region.
-
C.
Katherine Warren
Katherine Warren was an American character actress known for her supporting roles in mid-20th-century films and television.
-
D.
Katherine Scruse
Katherine Scruse is better known as Katherine Jackson, the matriarch of the Jackson family and mother of pop icon Michael Jackson.
-
E.
Katharine Blake
Katharine Blake was a British actress known for her work in mid-20th-century film and television, often portraying strong, dramatic characters.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d40ee08190b79d8e3d7f1b1272 |
completed | April 19, 2026, 3:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a047125683081908a18067ff3fd7956 |
completed | May 13, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_6a04730c241c8190800aa4c99dfa5c08 |
completed | May 13, 2026, 12:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0473c5c03c8190956a5d640cfd579d |
completed | May 13, 2026, 12:51 p.m. |
Created at: April 10, 2026, 5:49 a.m.