Triple
T17399603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hatchet |
E423051
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Sarah Elbert
Sarah Elbert is a film producer best known for her work on the horror movie "Hatchet."
|
E1371069
|
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: Sarah Elbert | Statement: [Hatchet, producer, Sarah Elbert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Elbert Context triple: [Hatchet, producer, Sarah Elbert]
-
A.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
-
B.
Sarah Bolger
Sarah Bolger is an Irish actress known for her roles in films like "In America" and "The Spiderwick Chronicles" and TV series such as "The Tudors" and "Once Upon a Time."
-
C.
Sarah Ulmer
Sarah Ulmer is a New Zealand former track cyclist and Olympic gold medallist renowned for breaking the individual pursuit world record.
-
D.
Sarah Roemer
Sarah Roemer is an American actress and former model best known for her role in the thriller film "Disturbia" and appearances in various television series and movies.
-
E.
Lisa Eilbacher
Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
- 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: Sarah Elbert Triple: [Hatchet, producer, Sarah Elbert]
Generated description
Sarah Elbert is a film producer best known for her work on the horror movie "Hatchet."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarah Elbert Target entity description: Sarah Elbert is a film producer best known for her work on the horror movie "Hatchet."
-
A.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
-
B.
Sarah Bolger
Sarah Bolger is an Irish actress known for her roles in films like "In America" and "The Spiderwick Chronicles" and TV series such as "The Tudors" and "Once Upon a Time."
-
C.
Sarah Ulmer
Sarah Ulmer is a New Zealand former track cyclist and Olympic gold medallist renowned for breaking the individual pursuit world record.
-
D.
Sarah Roemer
Sarah Roemer is an American actress and former model best known for her role in the thriller film "Disturbia" and appearances in various television series and movies.
-
E.
Lisa Eilbacher
Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43ac0596481908c400916d5c1b971 |
completed | April 19, 2026, 2:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a071bc0308081908f2b98b0dec96ab6 |
completed | May 15, 2026, 1:12 p.m. |
| NEDg | Description generation | batch_6a071c8a9dec8190a4fbb88736b73912 |
completed | May 15, 2026, 1:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a071e0e00208190a6e05266d5bc47e2 |
completed | May 15, 2026, 1:22 p.m. |
Created at: April 10, 2026, 5:45 a.m.