Triple
T3228498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edie Falco |
E67680
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Macy Falco
Macy Falco is the adopted daughter of American actress Edie Falco.
|
E338830
|
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: Macy Falco | Statement: [Edie Falco, hasChild, Macy Falco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macy Falco Context triple: [Edie Falco, hasChild, Macy Falco]
-
A.
Mia Dolan
Mia Dolan is an aspiring actress in Los Angeles and one of the two central protagonists of the musical film "La La Land."
-
B.
Madeline Neroni
Madeline Neroni is a captivating, manipulative, and physically disabled beauty in Anthony Trollope’s novel "Barchester Towers," known for using her charm and wit to influence the social and romantic intrigues around her.
-
C.
Maddy Bowen
Maddy Bowen is a determined American journalist in the film "Blood Diamond" who investigates the illicit diamond trade in war-torn Sierra Leone.
-
D.
Mia Zottoli
Mia Zottoli is an American actress and model known for her roles in late-1990s and early-2000s erotic thrillers and B-movies.
-
E.
Lacey Pemberton
Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
- 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: Macy Falco Triple: [Edie Falco, hasChild, Macy Falco]
Generated description
Macy Falco is the adopted daughter of American actress Edie Falco.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Macy Falco Target entity description: Macy Falco is the adopted daughter of American actress Edie Falco.
-
A.
Mia Dolan
Mia Dolan is an aspiring actress in Los Angeles and one of the two central protagonists of the musical film "La La Land."
-
B.
Madeline Neroni
Madeline Neroni is a captivating, manipulative, and physically disabled beauty in Anthony Trollope’s novel "Barchester Towers," known for using her charm and wit to influence the social and romantic intrigues around her.
-
C.
Maddy Bowen
Maddy Bowen is a determined American journalist in the film "Blood Diamond" who investigates the illicit diamond trade in war-torn Sierra Leone.
-
D.
Mia Zottoli
Mia Zottoli is an American actress and model known for her roles in late-1990s and early-2000s erotic thrillers and B-movies.
-
E.
Lacey Pemberton
Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaeb6f8588190a33a9d6c779e8992 |
completed | March 8, 2026, 5:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b262675b588190bcff98e7fa3a0c77 |
completed | March 12, 2026, 6:51 a.m. |
| NEDg | Description generation | batch_69b264c6022c81908b3235e88a7ed27f |
completed | March 12, 2026, 7:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b268bd0d3c8190a60dda0a9086c0cc |
completed | March 12, 2026, 7:18 a.m. |
Created at: March 8, 2026, 3:08 p.m.