Triple
T16457565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 50/50 |
E399720
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Barbara A. Hall |
—
|
NE NERFINISHED |
How this triple was built (2 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 A. Hall | Statement: [50/50, producer, Barbara A. Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barbara A. Hall Context triple: [50/50, producer, Barbara A. Hall]
-
A.
Barbara Hall
chosen
Barbara Hall is an American television writer and producer best known for creating series such as "Madam Secretary" and "Joan of Arcadia."
-
B.
Barbara Hall
Barbara Hall is a Canadian politician who served as the 60th mayor of Toronto in the 1990s and later became Ontario's chief commissioner of human rights.
-
C.
Barbara M. Rolph
Barbara M. Rolph was the woman who sponsored the U.S. Navy heavy cruiser USS San Francisco (CA-38) at its launching ceremony.
-
D.
Joan A. Brennecke
Joan A. Brennecke is a prominent chemical engineer renowned for her pioneering research on ionic liquids and sustainable chemical processes, recognized as one of the leading figures in green chemistry.
-
E.
Joan E. Chapman
Joan E. Chapman is a film editor known for her work on the action movie "First Blood."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d7ef5cc819084cfeb1a3e39d3cc |
completed | April 18, 2026, 7:06 a.m. |
Created at: April 10, 2026, 5:10 a.m.