Triple
T20232399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ark in Space |
E495559
|
entity |
| Predicate | starsActor |
P5563
|
FINISHED |
| Object |
Richardson Morgan
Richardson Morgan is an actor best known for his role in the classic 1975 Doctor Who serial "The Ark in Space."
|
E1418727
|
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: Richardson Morgan | Statement: [The Ark in Space, starsActor, Richardson Morgan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Richardson Morgan Context triple: [The Ark in Space, starsActor, Richardson Morgan]
-
A.
Lyttleton Morgan
Lyttleton Morgan was an influential figure in American education and religious life, notably serving as the first chairman of the board of trustees of what became Morgan State University.
-
B.
Sidney Morgan
Sidney Morgan is an actor known for appearing in the film adaptation of Sean O'Casey’s play "Juno and the Paycock."
-
C.
Tennyson Sanders
Tennyson Sanders is a child of British film director Rupert Sanders.
-
D.
Milner Gray
Milner Gray was a prominent British industrial designer and design consultant known for his influential role in shaping modern design practice in the mid-20th century.
-
E.
Barley Blair
Barley Blair is the disillusioned, hard-drinking British publisher who becomes an unlikely spy at the center of John le Carré’s Cold War novel "The Russia House."
- 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: Richardson Morgan Triple: [The Ark in Space, starsActor, Richardson Morgan]
Generated description
Richardson Morgan is an actor best known for his role in the classic 1975 Doctor Who serial "The Ark in Space."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Richardson Morgan Target entity description: Richardson Morgan is an actor best known for his role in the classic 1975 Doctor Who serial "The Ark in Space."
-
A.
Lyttleton Morgan
Lyttleton Morgan was an influential figure in American education and religious life, notably serving as the first chairman of the board of trustees of what became Morgan State University.
-
B.
Sidney Morgan
Sidney Morgan is an actor known for appearing in the film adaptation of Sean O'Casey’s play "Juno and the Paycock."
-
C.
Tennyson Sanders
Tennyson Sanders is a child of British film director Rupert Sanders.
-
D.
Milner Gray
Milner Gray was a prominent British industrial designer and design consultant known for his influential role in shaping modern design practice in the mid-20th century.
-
E.
Barley Blair
Barley Blair is the disillusioned, hard-drinking British publisher who becomes an unlikely spy at the center of John le Carré’s Cold War novel "The Russia House."
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fddafac819089cef4158f5e0ab5 |
completed | April 20, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a084b8e73908190a0c09697d6dc1c76 |
completed | May 16, 2026, 10:48 a.m. |
| NEDg | Description generation | batch_6a084c041b5c8190881a6d08c4afe42f |
completed | May 16, 2026, 10:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a084c7dee808190a0883f7f0c7873a9 |
completed | May 16, 2026, 10:52 a.m. |
Created at: April 11, 2026, 11:39 p.m.