Triple
T11830154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Marriage Clause |
E281365
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object |
Robert Agnew
Robert Agnew was an American silent film actor active in the 1920s, known for his boyish charm and roles in romantic dramas and comedies.
|
E950044
|
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: Robert Agnew | Statement: [The Marriage Clause, starredActor, Robert Agnew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Agnew Context triple: [The Marriage Clause, starredActor, Robert Agnew]
-
A.
Mark Agnew
Mark Agnew is a professional associated with Lakeside School as one of its notable alumni, recognized for his subsequent career achievements.
-
B.
Gabriel Almond
Gabriel Almond was an influential American political scientist known for his work on comparative politics and political culture.
-
C.
Theodore Spiros Agnew
Theodore Spiros Agnew was the Greek immigrant father of U.S. Vice President Spiro Agnew, known primarily through his son's political prominence.
-
D.
Michael Foster
Michael Foster is a songwriter best known for co-writing Ariana Grande’s hit single "thank u, next."
-
E.
James Acheson
James Acheson is an acclaimed British costume designer best known for his Oscar-winning work on films such as "The Last Emperor" and "Dangerous Liaisons."
- 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: Robert Agnew Triple: [The Marriage Clause, starredActor, Robert Agnew]
Generated description
Robert Agnew was an American silent film actor active in the 1920s, known for his boyish charm and roles in romantic dramas and comedies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Robert Agnew Target entity description: Robert Agnew was an American silent film actor active in the 1920s, known for his boyish charm and roles in romantic dramas and comedies.
-
A.
Mark Agnew
Mark Agnew is a professional associated with Lakeside School as one of its notable alumni, recognized for his subsequent career achievements.
-
B.
Gabriel Almond
Gabriel Almond was an influential American political scientist known for his work on comparative politics and political culture.
-
C.
Theodore Spiros Agnew
Theodore Spiros Agnew was the Greek immigrant father of U.S. Vice President Spiro Agnew, known primarily through his son's political prominence.
-
D.
Michael Foster
Michael Foster is a songwriter best known for co-writing Ariana Grande’s hit single "thank u, next."
-
E.
James Acheson
James Acheson is an acclaimed British costume designer best known for his Oscar-winning work on films such as "The Last Emperor" and "Dangerous Liaisons."
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62b75dc8190b27d24e46a262a11 |
completed | April 10, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f1672e736481909ba5f867cb840039 |
completed | April 29, 2026, 2:04 a.m. |
| NEDg | Description generation | batch_69f170034b488190a6976d3333823caa |
completed | April 29, 2026, 2:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f17805325881908b98eb9c8fc59778 |
completed | April 29, 2026, 3:16 a.m. |
Created at: April 8, 2026, 9:43 p.m.