Triple
T9839609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Specialist |
E239187
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Alexandra Seros
Alexandra Seros is a screenwriter best known for her work on action and thriller films in Hollywood.
|
E825613
|
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: Alexandra Seros | Statement: [The Specialist, screenwriter, Alexandra Seros]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexandra Seros Context triple: [The Specialist, screenwriter, Alexandra Seros]
-
A.
Alexandra Saks
Alexandra Saks is a film producer recognized for her work on independent and studio-backed feature films.
-
B.
Alix Pahlavouni
Alix Pahlavouni was a noblewoman of the Armenian Kingdom of Cilicia and a member of the influential Pahlavuni family, known primarily as the queen consort and mother of King Hethum I.
-
C.
Alexandra Byrne
Alexandra Byrne is an acclaimed British costume designer known for her intricate period costumes and award-winning work in both film and theatre.
-
D.
Alexandra Rubenstein
Alexandra Rubenstein is one of the daughters of American billionaire investor and philanthropist David M. Rubenstein.
-
E.
Alexandra Adi
Alexandra Adi is an American actress known for her supporting roles in films and television series during the 1990s and early 2000s.
- 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: Alexandra Seros Triple: [The Specialist, screenwriter, Alexandra Seros]
Generated description
Alexandra Seros is a screenwriter best known for her work on action and thriller films in Hollywood.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alexandra Seros Target entity description: Alexandra Seros is a screenwriter best known for her work on action and thriller films in Hollywood.
-
A.
Alexandra Saks
Alexandra Saks is a film producer recognized for her work on independent and studio-backed feature films.
-
B.
Alix Pahlavouni
Alix Pahlavouni was a noblewoman of the Armenian Kingdom of Cilicia and a member of the influential Pahlavuni family, known primarily as the queen consort and mother of King Hethum I.
-
C.
Alexandra Byrne
Alexandra Byrne is an acclaimed British costume designer known for her intricate period costumes and award-winning work in both film and theatre.
-
D.
Alexandra Rubenstein
Alexandra Rubenstein is one of the daughters of American billionaire investor and philanthropist David M. Rubenstein.
-
E.
Alexandra Adi
Alexandra Adi is an American actress known for her supporting roles in films and television series during the 1990s and early 2000s.
- 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb34b045481908f89abd576aab497 |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e429682c8190a94339b96d4081f6 |
completed | April 5, 2026, 4:25 a.m. |
| NEDg | Description generation | batch_69d1e50214888190a93a9a27cc3f203f |
completed | April 5, 2026, 4:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1e5659fd88190bcee1dc2851df117 |
completed | April 5, 2026, 4:30 a.m. |
Created at: March 30, 2026, 8:33 p.m.