Triple
T6126701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Water for Elephants |
E136612
|
entity |
| Predicate | authorOfSourceMaterial |
P2806
|
FINISHED |
| Object |
Sara Gruen
Sara Gruen is a Canadian-American novelist best known for her bestselling historical novel "Water for Elephants."
|
E571375
|
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: Sara Gruen | Statement: [Water for Elephants, authorOfSourceMaterial, Sara Gruen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sara Gruen Context triple: [Water for Elephants, authorOfSourceMaterial, Sara Gruen]
-
A.
Francine Rivers
Francine Rivers is a bestselling American author known for her inspirational Christian fiction novels, particularly "Redeeming Love."
-
B.
Sandra Grant
Sandra Grant is an American actress best known for her long-term marriage to legendary singer Tony Bennett.
-
C.
Paulette Jiles
Paulette Jiles is an American poet and novelist best known for her historical fiction, including the novel "News of the World."
-
D.
Beth Winters
Beth Winters is a fictional character from the 2012 ensemble drama-comedy film "Darling Companion."
-
E.
Jodi Picoult
Jodi Picoult is a bestselling American author known for her emotionally charged novels that tackle complex moral and social issues.
- 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: Sara Gruen Triple: [Water for Elephants, authorOfSourceMaterial, Sara Gruen]
Generated description
Sara Gruen is a Canadian-American novelist best known for her bestselling historical novel "Water for Elephants."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sara Gruen Target entity description: Sara Gruen is a Canadian-American novelist best known for her bestselling historical novel "Water for Elephants."
-
A.
Francine Rivers
Francine Rivers is a bestselling American author known for her inspirational Christian fiction novels, particularly "Redeeming Love."
-
B.
Sandra Grant
Sandra Grant is an American actress best known for her long-term marriage to legendary singer Tony Bennett.
-
C.
Paulette Jiles
Paulette Jiles is an American poet and novelist best known for her historical fiction, including the novel "News of the World."
-
D.
Beth Winters
Beth Winters is a fictional character from the 2012 ensemble drama-comedy film "Darling Companion."
-
E.
Jodi Picoult
Jodi Picoult is a bestselling American author known for her emotionally charged novels that tackle complex moral and social issues.
- 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_69c008a0a37c81908e5b4f879158afb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c2a13a48190b80e11d58fc87c8a |
completed | March 22, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c135bd8d3881909873d2a063b3aecc |
completed | March 23, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_69c1392b0e448190846ccf73e89a6ad3 |
completed | March 23, 2026, 12:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c139884ba881908db94f17d8d97faf |
completed | March 23, 2026, 1 p.m. |
Created at: March 22, 2026, 4:15 p.m.