Triple
T2169757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Woods |
E48393
|
entity |
| Predicate | portrayedCharacter |
P1668
|
FINISHED |
| Object |
Sebastian Stark in Shark
Sebastian Stark in "Shark" is a brilliant, hard-driving Los Angeles prosecutor known for his ruthless tactics and sharp courtroom strategies.
|
E239196
|
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: Sebastian Stark in Shark | Statement: [James Woods, portrayedCharacter, Sebastian Stark in Shark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sebastian Stark in Shark Context triple: [James Woods, portrayedCharacter, Sebastian Stark in Shark]
-
A.
Sebastian
Sebastian is a masculine given name of Latin origin, commonly used in many European and English-speaking countries.
-
B.
Sebastian Blunt
Sebastian Blunt is a British actor and the brother of acclaimed actress Emily Blunt.
-
C.
Kai Dugan
Kai Dugan is the son of American actress Jennifer Connelly, known primarily for his connection to his famous mother.
-
D.
Dan Stark
Dan Stark is a fictional, rule-bending veteran detective from the TV series "The Good Guys," portrayed by actor Bradley Whitford.
-
E.
Hudson Fysh
Hudson Fysh was an Australian aviator and businessman best known as a co-founder and long-serving leader of Qantas, helping to establish it as a major international airline.
- 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: Sebastian Stark in Shark Triple: [James Woods, portrayedCharacter, Sebastian Stark in Shark]
Generated description
Sebastian Stark in "Shark" is a brilliant, hard-driving Los Angeles prosecutor known for his ruthless tactics and sharp courtroom strategies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sebastian Stark in Shark Target entity description: Sebastian Stark in "Shark" is a brilliant, hard-driving Los Angeles prosecutor known for his ruthless tactics and sharp courtroom strategies.
-
A.
Sebastian
Sebastian is a masculine given name of Latin origin, commonly used in many European and English-speaking countries.
-
B.
Sebastian Blunt
Sebastian Blunt is a British actor and the brother of acclaimed actress Emily Blunt.
-
C.
Kai Dugan
Kai Dugan is the son of American actress Jennifer Connelly, known primarily for his connection to his famous mother.
-
D.
Dan Stark
Dan Stark is a fictional, rule-bending veteran detective from the TV series "The Good Guys," portrayed by actor Bradley Whitford.
-
E.
Hudson Fysh
Hudson Fysh was an Australian aviator and businessman best known as a co-founder and long-serving leader of Qantas, helping to establish it as a major international airline.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbeaeb58881908ad34f7b253bac2a |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58f511a08190880fbde8900d59df |
completed | March 9, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69ae59a9b010819081491e988184b386 |
completed | March 9, 2026, 5:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5a12f11c81908cc345905f0a485e |
completed | March 9, 2026, 5:26 a.m. |
Created at: March 4, 2026, 7:45 p.m.