Triple
T16007316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Austen |
E388251
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Jeffrey Lieber |
E388250
|
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: Jeffrey Lieber | Statement: [Kate Austen, createdBy, Jeffrey Lieber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Lieber Context triple: [Kate Austen, createdBy, Jeffrey Lieber]
-
A.
Jeffrey Lieber
chosen
Jeffrey Lieber is an American screenwriter and producer best known for his early role in developing the hit television series "Lost."
-
B.
Douglas Fackler
Douglas Fackler is a bumbling, mild-mannered police cadet character from the "Police Academy" comedy film series.
-
C.
Michael Glouberman
Michael Glouberman is a television writer and producer best known for his work on the acclaimed sitcom "Malcolm in the Middle."
-
D.
Aaron Heilman
Aaron Heilman is a former American Major League Baseball pitcher best known for his years with the New York Mets in the 2000s.
-
E.
Benjamin J. Hubbard
Benjamin J. Hubbard is an American scholar of religious studies known for his work on religion in public life and contemporary religious issues.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15800246c8190a298c5f96478c396 |
completed | April 16, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff293c2248190993d5d74eaf626bc |
completed | May 10, 2026, 2:50 a.m. |
Created at: April 10, 2026, 4:55 a.m.