Triple
T2129471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hart of Dixie |
E46503
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Leila Gerstein |
E240305
|
NE FINISHED |
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: Leila Gerstein | Statement: [Hart of Dixie, developer, Leila Gerstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leila Gerstein Context triple: [Hart of Dixie, developer, Leila Gerstein]
-
A.
Leila Gerstein
chosen
Leila Gerstein is an American television writer and producer best known for creating the comedy-drama series "Hart of Dixie."
-
B.
Esther Raab
Esther Raab was a Jewish Holocaust survivor known for escaping from the Sobibor extermination camp and later bearing witness to its atrocities.
-
C.
Elsa Löwenthal
Elsa Löwenthal, better known as Elsa Einstein, was the second wife and cousin of physicist Albert Einstein and often managed his personal and social affairs.
-
D.
Herta Amir
Herta Amir is a benefactor whose philanthropy is commemorated through the naming of the Herta and Paul Amir Building.
-
E.
Jeanne Rosenberg
Jeanne Rosenberg is an American screenwriter best known for her work on the acclaimed 1979 film adaptation of "The Black Stallion" and other family-oriented adventure films.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb77ccc4819087bee5dbb91b5ae8 |
completed | March 7, 2026, 5:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71ac8a0081909cbb1187513bfc56 |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:44 p.m.