Triple
T3786312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lost |
E85538
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object |
Jeffrey Lieber
Jeffrey Lieber is an American screenwriter and producer best known for his early role in developing the hit television series "Lost."
|
E388250
|
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: Jeffrey Lieber | Statement: [Lost, creator, Jeffrey Lieber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Lieber Context triple: [Lost, creator, Jeffrey Lieber]
-
A.
Andrew Weisblum
Andrew Weisblum is an American film editor known for his work on major feature films, including collaborations with directors like Darren Aronofsky and Wes Anderson.
-
B.
Todd Lieberman
Todd Lieberman is an American film producer known for his work on acclaimed movies such as "The Fighter" and other major Hollywood productions.
-
C.
Jeffrey Auerbach
Jeffrey Auerbach is a film producer best known for his work on the stop-motion animated feature "Corpse Bride."
-
D.
Michael B. Gerrard
Michael B. Gerrard is an American environmental lawyer and scholar known for his leadership in climate change law and policy.
-
E.
Bryan Goluboff
Bryan Goluboff is an American screenwriter and playwright best known for his work on the film adaptation of Jim Carroll’s memoir "The Basketball Diaries."
- 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: Jeffrey Lieber Triple: [Lost, creator, Jeffrey Lieber]
Generated description
Jeffrey Lieber is an American screenwriter and producer best known for his early role in developing the hit television series "Lost."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Lieber Target entity description: Jeffrey Lieber is an American screenwriter and producer best known for his early role in developing the hit television series "Lost."
-
A.
Andrew Weisblum
Andrew Weisblum is an American film editor known for his work on major feature films, including collaborations with directors like Darren Aronofsky and Wes Anderson.
-
B.
Todd Lieberman
Todd Lieberman is an American film producer known for his work on acclaimed movies such as "The Fighter" and other major Hollywood productions.
-
C.
Jeffrey Auerbach
Jeffrey Auerbach is a film producer best known for his work on the stop-motion animated feature "Corpse Bride."
-
D.
Michael B. Gerrard
Michael B. Gerrard is an American environmental lawyer and scholar known for his leadership in climate change law and policy.
-
E.
Bryan Goluboff
Bryan Goluboff is an American screenwriter and playwright best known for his work on the film adaptation of Jim Carroll’s memoir "The Basketball Diaries."
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee42d2bc88190ab85529fcd1aa20a |
completed | March 9, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f04ceea881909c3f0d1da9b538ae |
completed | March 14, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69b4f1730bbc8190a2f5f70ebc5a528a |
completed | March 14, 2026, 5:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4f2538eac81908a6c85ddab4e2356 |
completed | March 14, 2026, 5:29 a.m. |
Created at: March 9, 2026, 3:13 p.m.