Triple
T7809373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grandma's Boy |
E180638
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Anna Townsend
Anna Townsend was an American character actress best known for her comedic role as the foul-mouthed grandmother in the film "Grandma's Boy."
|
E694541
|
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: Anna Townsend | Statement: [Grandma's Boy, starring, Anna Townsend]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Townsend Context triple: [Grandma's Boy, starring, Anna Townsend]
-
A.
Emma T. Townsend
Emma T. Townsend was the wife of prominent American steel industry magnate and U.S. Steel co-founder Elbert H. Gary.
-
B.
Mathilde Townsend
Mathilde Townsend was an American socialite and Washington, D.C. hostess prominent in early 20th-century political and diplomatic circles.
-
C.
Anne Wheeler
Anne Wheeler is a fictional trapeze artist and acrobat featured in the musical film "The Greatest Showman."
-
D.
Charlotte Leslie
Charlotte Leslie is a British Conservative politician who served as the Member of Parliament for Bristol North West from 2010 to 2017.
-
E.
Katharine Towne
Katharine Towne is an American actress known for her roles in films such as "She's All That," "Mulholland Drive," and "What Lies Beneath."
- 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: Anna Townsend Triple: [Grandma's Boy, starring, Anna Townsend]
Generated description
Anna Townsend was an American character actress best known for her comedic role as the foul-mouthed grandmother in the film "Grandma's Boy."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anna Townsend Target entity description: Anna Townsend was an American character actress best known for her comedic role as the foul-mouthed grandmother in the film "Grandma's Boy."
-
A.
Emma T. Townsend
Emma T. Townsend was the wife of prominent American steel industry magnate and U.S. Steel co-founder Elbert H. Gary.
-
B.
Mathilde Townsend
Mathilde Townsend was an American socialite and Washington, D.C. hostess prominent in early 20th-century political and diplomatic circles.
-
C.
Anne Wheeler
Anne Wheeler is a fictional trapeze artist and acrobat featured in the musical film "The Greatest Showman."
-
D.
Charlotte Leslie
Charlotte Leslie is a British Conservative politician who served as the Member of Parliament for Bristol North West from 2010 to 2017.
-
E.
Katharine Towne
Katharine Towne is an American actress known for her roles in films such as "She's All That," "Mulholland Drive," and "What Lies Beneath."
- 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78bb4b08190b2b3b51c5a0a033c |
completed | March 30, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb145b93788190a89f26dacbd0b437 |
completed | March 31, 2026, 12:24 a.m. |
| NEDg | Description generation | batch_69cb173190a88190b31fd7973bc19d43 |
completed | March 31, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a56d25881908b8413b82edf5508 |
completed | March 31, 2026, 12:50 a.m. |
Created at: March 30, 2026, 4:36 p.m.