Triple
T13431234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green family |
E313614
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object |
Barbara Green
Barbara Green is an individual associated with the Green family, known primarily as one of its members.
|
E1040605
|
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: Barbara Green | Statement: [Green family, member, Barbara Green]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barbara Green Context triple: [Green family, member, Barbara Green]
-
A.
Sally Greenberg
Sally Greenberg is a consumer rights advocate and attorney who serves as a leading executive of the National Consumers League, focusing on protecting and promoting consumer interests.
-
B.
Gillian Greene
Gillian Greene is an American actress and filmmaker, known for her work in film and television and for being married to director Sam Raimi.
-
C.
Patricia Greene
Patricia Greene is a British actress best known for her long-running role as Jill Archer in the BBC radio soap opera "The Archers."
-
D.
Arline Greenbaum
Arline Greenbaum was the first wife of physicist Richard Feynman, remembered for their deeply devoted relationship during her struggle with tuberculosis in the 1940s.
-
E.
Helen Green
Helen Green is known as the wife of former U.S. Congressman Gene Green.
- 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: Barbara Green Triple: [Green family, member, Barbara Green]
Generated description
Barbara Green is an individual associated with the Green family, known primarily as one of its members.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barbara Green Target entity description: Barbara Green is an individual associated with the Green family, known primarily as one of its members.
-
A.
Sally Greenberg
Sally Greenberg is a consumer rights advocate and attorney who serves as a leading executive of the National Consumers League, focusing on protecting and promoting consumer interests.
-
B.
Gillian Greene
Gillian Greene is an American actress and filmmaker, known for her work in film and television and for being married to director Sam Raimi.
-
C.
Patricia Greene
Patricia Greene is a British actress best known for her long-running role as Jill Archer in the BBC radio soap opera "The Archers."
-
D.
Arline Greenbaum
Arline Greenbaum was the first wife of physicist Richard Feynman, remembered for their deeply devoted relationship during her struggle with tuberculosis in the 1940s.
-
E.
Helen Green
Helen Green is known as the wife of former U.S. Congressman Gene Green.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed41a5481908800033303224adb |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7398b828c8190a029a5862ae1fded |
completed | May 3, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69f73b065818819095d26633fc682546 |
completed | May 3, 2026, 12:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f73b8635888190b31035bc72676b9d |
completed | May 3, 2026, 12:11 p.m. |
Created at: April 9, 2026, 9:40 p.m.