Triple
T14397521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three Men and a Baby |
E356987
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Michelle Amini
Michelle Amini is an actress known for appearing in the popular 1987 comedy film "Three Men and a Baby."
|
E1096635
|
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: Michelle Amini | Statement: [Three Men and a Baby, castMember, Michelle Amini]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle Amini Context triple: [Three Men and a Baby, castMember, Michelle Amini]
-
A.
Alexandra Amini
Alexandra Amini is an actress known for appearing in the popular 1987 comedy film "Three Men and a Baby."
-
B.
Soraya Nazarian
Soraya Nazarian is an Iranian-born American sculptor and philanthropist known for her cultural and educational contributions, particularly within the Jewish and Israeli communities.
-
C.
Sia Alipour
Sia Alipour is an actor known for his role in the Iranian television series "Tehran."
-
D.
Susan Motamed
Susan Motamed is a film producer best known for her work on the acclaimed documentary "Enron: The Smartest Guys in the Room."
-
E.
Sarah Solemani
Sarah Solemani is a British actress and writer known for her roles in television comedies like "Him & Her" and "Bad Education" as well as various film and stage performances.
- 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: Michelle Amini Triple: [Three Men and a Baby, castMember, Michelle Amini]
Generated description
Michelle Amini is an actress known for appearing in the popular 1987 comedy film "Three Men and a Baby."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michelle Amini Target entity description: Michelle Amini is an actress known for appearing in the popular 1987 comedy film "Three Men and a Baby."
-
A.
Alexandra Amini
chosen
Alexandra Amini is an actress known for appearing in the popular 1987 comedy film "Three Men and a Baby."
-
B.
Soraya Nazarian
Soraya Nazarian is an Iranian-born American sculptor and philanthropist known for her cultural and educational contributions, particularly within the Jewish and Israeli communities.
-
C.
Sia Alipour
Sia Alipour is an actor known for his role in the Iranian television series "Tehran."
-
D.
Susan Motamed
Susan Motamed is a film producer best known for her work on the acclaimed documentary "Enron: The Smartest Guys in the Room."
-
E.
Sarah Solemani
Sarah Solemani is a British actress and writer known for her roles in television comedies like "Him & Her" and "Bad Education" as well as various film and stage performances.
- F. None of above.
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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90826f908190b3969af9b7cf922f |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bc424f88190ab3a1c1aec61cb40 |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5cf4dedc81908988f13f0fc9f510 |
completed | May 8, 2026, 3:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5dcf151c8190959b3240813a1d71 |
completed | May 8, 2026, 3:51 a.m. |
Created at: April 10, 2026, 1:17 a.m.