Triple
T2624782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Secretary |
E59091
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object |
Barbara Hall
Barbara Hall is an American television writer and producer best known for creating series such as "Madam Secretary" and "Joan of Arcadia."
|
E513537
|
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 Hall | Statement: [Madame Secretary, creator, Barbara Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barbara Hall Context triple: [Madame Secretary, creator, Barbara Hall]
-
A.
Barbara Cherry
Barbara Cherry was the wife of renowned German-American astronomer Martin Schwarzschild.
-
B.
Barbara Enberg
Barbara Enberg is known as the wife of the late American sportscaster Dick Enberg.
-
C.
Barbara McDougall
Barbara McDougall is a Canadian politician and former Progressive Conservative cabinet minister who served prominently in federal government roles in the late 20th century.
-
D.
Barbara Heinzen
Barbara Heinzen was the wife of William Colby, the former Director of Central Intelligence of the United States.
-
E.
Maureen Swanson
Maureen Swanson was a British actress active in the 1950s, known for her roles in comedy and drama films before later becoming the Countess of Dudley.
- 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 Hall Triple: [Madame Secretary, creator, Barbara Hall]
Generated description
Barbara Hall is an American television writer and producer best known for creating series such as "Madam Secretary" and "Joan of Arcadia."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barbara Hall Target entity description: Barbara Hall is an American television writer and producer best known for creating series such as "Madam Secretary" and "Joan of Arcadia."
-
A.
Barbara Cherry
Barbara Cherry was the wife of renowned German-American astronomer Martin Schwarzschild.
-
B.
Barbara Enberg
Barbara Enberg is known as the wife of the late American sportscaster Dick Enberg.
-
C.
Barbara McDougall
Barbara McDougall is a Canadian politician and former Progressive Conservative cabinet minister who served prominently in federal government roles in the late 20th century.
-
D.
Barbara Heinzen
Barbara Heinzen was the wife of William Colby, the former Director of Central Intelligence of the United States.
-
E.
Maureen Swanson
Maureen Swanson was a British actress active in the 1950s, known for her roles in comedy and drama films before later becoming the Countess of Dudley.
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8b061a08190b7a8459851abaae2 |
completed | March 7, 2026, 7:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf219021d081909d814d0dbf564501 |
completed | March 21, 2026, 10:54 p.m. |
| NEDg | Description generation | batch_69bf22669b4081909a0126e0d8e69fd2 |
completed | March 21, 2026, 10:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf232ed3508190880aab032f8f0b34 |
completed | March 21, 2026, 11:01 p.m. |
Created at: March 6, 2026, 9:50 p.m.