Triple
T12090257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Into the Badlands |
E287922
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Oliver Stark
Oliver Stark is a British actor best known for his television roles in action and drama series, including prominent parts in shows like "Into the Badlands" and "9-1-1."
|
E528707
|
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: Oliver Stark | Statement: [Into the Badlands, starring, Oliver Stark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oliver Stark Context triple: [Into the Badlands, starring, Oliver Stark]
-
A.
Oliver Stark
Oliver Stark is a British actor best known for playing firefighter Evan "Buck" Buckley on the television drama series 9-1-1.
-
B.
Oliver Lambert
Oliver Lambert is the protagonist of the legal thriller "The Firm," around whom the story’s central conflicts and developments revolve.
-
C.
Oliver Johnson
Oliver Johnson was a prominent 19th-century American abolitionist, editor, and reformer active in the anti-slavery movement.
-
D.
Oliver Nolan
Oliver Nolan is one of the children of British film producer Emma Thomas and her husband, acclaimed director Christopher Nolan.
-
E.
Oliver Stapleton
Oliver Stapleton is a British cinematographer known for his versatile work across acclaimed films in both independent and mainstream cinema.
- 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: Oliver Stark Triple: [Into the Badlands, starring, Oliver Stark]
Generated description
Oliver Stark is a British actor best known for his television roles in action and drama series, including prominent parts in shows like "Into the Badlands" and "9-1-1."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oliver Stark Target entity description: Oliver Stark is a British actor best known for his television roles in action and drama series, including prominent parts in shows like "Into the Badlands" and "9-1-1."
-
A.
Oliver Stark
chosen
Oliver Stark is a British actor best known for playing firefighter Evan "Buck" Buckley on the television drama series 9-1-1.
-
B.
Oliver Lambert
Oliver Lambert is the protagonist of the legal thriller "The Firm," around whom the story’s central conflicts and developments revolve.
-
C.
Oliver Johnson
Oliver Johnson was a prominent 19th-century American abolitionist, editor, and reformer active in the anti-slavery movement.
-
D.
Oliver Nolan
Oliver Nolan is one of the children of British film producer Emma Thomas and her husband, acclaimed director Christopher Nolan.
-
E.
Oliver Stapleton
Oliver Stapleton is a British cinematographer known for his versatile work across acclaimed films in both independent and mainstream cinema.
- F. None of above.
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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915161f848190a6355c1e372eadaa |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f66b2eb48190bae469d1dd82b119 |
completed | May 2, 2026, 1:04 p.m. |
| NEDg | Description generation | batch_69f5fd79da748190b3f0dd7d7a46314d |
completed | May 2, 2026, 1:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5feeeeb2081908191b1c2d1c2fbfd |
completed | May 2, 2026, 1:41 p.m. |
Created at: April 8, 2026, 9:48 p.m.