Triple
T6661973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All or Nothing |
E151497
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Alison Garland
Alison Garland is a British actress best known for her role in Mike Leigh’s film "All or Nothing."
|
E633977
|
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: Alison Garland | Statement: [All or Nothing, stars, Alison Garland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alison Garland Context triple: [All or Nothing, stars, Alison Garland]
-
A.
Alison Porter
Alison Porter is a central character in John Osborne’s play "Look Back in Anger," portrayed as the emotionally conflicted and long-suffering wife of the protagonist, Jimmy Porter.
-
B.
Alison Brown
Alison Brown is a film industry professional best known for her role in founding the American animation company Blue Sky Studios.
-
C.
Alison Owen
Alison Owen is a British film producer known for acclaimed works such as "Elizabeth," "Shaun of the Dead," and "Saving Mr. Banks."
-
D.
Alison Arngrim
Alison Arngrim is an American actress and author best known for her iconic portrayal of the scheming Nellie Oleson on the classic television series "Little House on the Prairie."
-
E.
Alison Doody
Alison Doody is an Irish actress and former model best known for her role as Dr. Elsa Schneider in the film "Indiana Jones and the Last Crusade."
- 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: Alison Garland Triple: [All or Nothing, stars, Alison Garland]
Generated description
Alison Garland is a British actress best known for her role in Mike Leigh’s film "All or Nothing."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alison Garland Target entity description: Alison Garland is a British actress best known for her role in Mike Leigh’s film "All or Nothing."
-
A.
Alison Porter
Alison Porter is a central character in John Osborne’s play "Look Back in Anger," portrayed as the emotionally conflicted and long-suffering wife of the protagonist, Jimmy Porter.
-
B.
Alison Brown
Alison Brown is a film industry professional best known for her role in founding the American animation company Blue Sky Studios.
-
C.
Alison Owen
Alison Owen is a British film producer known for acclaimed works such as "Elizabeth," "Shaun of the Dead," and "Saving Mr. Banks."
-
D.
Alison Arngrim
Alison Arngrim is an American actress and author best known for her iconic portrayal of the scheming Nellie Oleson on the classic television series "Little House on the Prairie."
-
E.
Alison Doody
Alison Doody is an Irish actress and former model best known for her role as Dr. Elsa Schneider in the film "Indiana Jones and the Last Crusade."
- 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_69c687f5fac48190a09e4838d9c6b45d |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b097e0e481909251443f9ce0b85a |
completed | March 27, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7616ff6fc8190b4e9e7810be9064b |
completed | March 28, 2026, 5:04 a.m. |
| NEDg | Description generation | batch_69c764224d1c81909a0a631e284eb9d6 |
completed | March 28, 2026, 5:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76485b7748190b873b3701178201d |
completed | March 28, 2026, 5:17 a.m. |
Created at: March 27, 2026, 2:02 p.m.