Triple
T11460400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colin Morgan |
E271641
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Legend
Legend is a dramatic film in which Colin Morgan appears, known for its portrayal of the notorious Kray twins in 1960s London.
|
E927760
|
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: Legend | Statement: [Colin Morgan, notableWork, Legend]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Legend Context triple: [Colin Morgan, notableWork, Legend]
-
A.
Legend
Legend is a 1985 dark fantasy film directed by Ridley Scott, known for its lush visual style, fairy-tale atmosphere, and Tim Curry’s iconic portrayal of the Lord of Darkness.
-
B.
Legend
Legend was the original brand name of the Chinese technology company now known globally as Lenovo.
-
C.
Legend
Legend is a greatest hits compilation album by Bob Marley and the Wailers that has become one of the best-selling and most influential reggae records of all time.
-
D.
Legend
Legend is the official mascot character created for the 2015 World Aquatics Championships held in Kazan, Russia.
-
E.
Legend
Legend is a musical artist known for creating tracks like "Dope" within contemporary hip-hop and rap scenes.
- 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: Legend Triple: [Colin Morgan, notableWork, Legend]
Generated description
Legend is a dramatic film in which Colin Morgan appears, known for its portrayal of the notorious Kray twins in 1960s London.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Legend Target entity description: Legend is a dramatic film in which Colin Morgan appears, known for its portrayal of the notorious Kray twins in 1960s London.
-
A.
Legend
Legend is a 1985 dark fantasy film directed by Ridley Scott, known for its lush visual style, fairy-tale atmosphere, and Tim Curry’s iconic portrayal of the Lord of Darkness.
-
B.
Legend
Legend is a performer known for their role in the work "Nervous."
-
C.
Legend
Legend is a greatest hits compilation album by Bob Marley and the Wailers that has become one of the best-selling and most influential reggae records of all time.
-
D.
Legend
Legend is a musical artist known for creating tracks like "Dope" within contemporary hip-hop and rap scenes.
-
E.
Legend
Legend is the eighth studio album by American singer John Legend, showcasing his blend of R&B, soul, and pop influences.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f384f08190b1150ed1389dd31a |
completed | April 9, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e91f1bb881909a9c36d837e4059b |
completed | April 20, 2026, 8:51 a.m. |
| NEDg | Description generation | batch_69e5f1593c2c8190885f80ad5eeba3ec |
completed | April 20, 2026, 9:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5f87bbd988190ac388a3c34b2e95a |
completed | April 20, 2026, 9:57 a.m. |
Created at: April 8, 2026, 9:35 p.m.