Triple
T1804815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Silverberg |
E40196
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Karen Haber
Karen Haber is an American science fiction and fantasy author and editor known for her novels, short stories, and work on genre anthologies and criticism.
|
E212895
|
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: Karen Haber | Statement: [Robert Silverberg, spouse, Karen Haber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karen Haber Context triple: [Robert Silverberg, spouse, Karen Haber]
-
A.
Ann Rosener
Ann Rosener was an American photographer best known for her documentary images of home-front life and industry during World War II, particularly through her work for U.S. government agencies.
-
B.
Barbara Robbins
Barbara Robbins is known as the wife of Jon Lindbergh, the son of famed aviator Charles Lindbergh.
-
C.
Deborah Pines
Deborah Pines is an American physician and writer best known as the wife of journalist and author Tony Schwartz.
-
D.
Roberta Seidman
Roberta Seidman was the wife of American actor John Garfield, a prominent film star of the 1930s and 1940s.
-
E.
Deborah Waxman
Deborah Waxman is an American rabbi and scholar who serves as a leading contemporary voice and institutional leader within Reconstructionist Judaism.
- 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: Karen Haber Triple: [Robert Silverberg, spouse, Karen Haber]
Generated description
Karen Haber is an American science fiction and fantasy author and editor known for her novels, short stories, and work on genre anthologies and criticism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karen Haber Target entity description: Karen Haber is an American science fiction and fantasy author and editor known for her novels, short stories, and work on genre anthologies and criticism.
-
A.
Ann Rosener
Ann Rosener was an American photographer best known for her documentary images of home-front life and industry during World War II, particularly through her work for U.S. government agencies.
-
B.
Barbara Robbins
Barbara Robbins is known as the wife of Jon Lindbergh, the son of famed aviator Charles Lindbergh.
-
C.
Deborah Pines
Deborah Pines is an American physician and writer best known as the wife of journalist and author Tony Schwartz.
-
D.
Roberta Seidman
Roberta Seidman was the wife of American actor John Garfield, a prominent film star of the 1930s and 1940s.
-
E.
Deborah Waxman
Deborah Waxman is an American rabbi and scholar who serves as a leading contemporary voice and institutional leader within Reconstructionist Judaism.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa659648e8819085fafb60dc03f14b |
completed | March 6, 2026, 5:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adead0fb988190b403f5c62cbe991a |
completed | March 8, 2026, 9:32 p.m. |
| NEDg | Description generation | batch_69adeb5118608190be99a12b7f6b97c5 |
completed | March 8, 2026, 9:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adec25a87081908f098df81de6eafb |
completed | March 8, 2026, 9:37 p.m. |
Created at: March 4, 2026, 7:32 p.m.