Triple
T15927072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The 4400 |
E386229
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Laura Allen
Laura Allen is an American actress best known for her role as Lily Moore on the science fiction television series "The 4400."
|
E1184842
|
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: Laura Allen | Statement: [The 4400, portrayedBy, Laura Allen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Allen Context triple: [The 4400, portrayedBy, Laura Allen]
-
A.
Amy Allen
Amy Allen is an American philosopher known for her work in critical theory, feminism, and social and political philosophy.
-
B.
Amy Allen
Amy Allen is an American songwriter and singer known for penning hit pop songs for major artists such as Harry Styles, Halsey, and Selena Gomez.
-
C.
Janis Allen
Janis Allen is a screenwriter best known for co-writing the 1979 comedy film "Meatballs."
-
D.
Audra Lindley
Audra Lindley was an American actress best known for her role as the quirky landlady Helen Roper on the television sitcom "Three's Company" and its spin-off "The Ropers."
-
E.
Laura Rister
Laura Rister is a film producer and executive known for her work on independent and prestige projects, including the financial thriller "Margin Call."
- 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: Laura Allen Triple: [The 4400, portrayedBy, Laura Allen]
Generated description
Laura Allen is an American actress best known for her role as Lily Moore on the science fiction television series "The 4400."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laura Allen Target entity description: Laura Allen is an American actress best known for her role as Lily Moore on the science fiction television series "The 4400."
-
A.
Amy Allen
Amy Allen is an American philosopher known for her work in critical theory, feminism, and social and political philosophy.
-
B.
Amy Allen
Amy Allen is an American songwriter and singer known for penning hit pop songs for major artists such as Harry Styles, Halsey, and Selena Gomez.
-
C.
Janis Allen
Janis Allen is a screenwriter best known for co-writing the 1979 comedy film "Meatballs."
-
D.
Audra Lindley
Audra Lindley was an American actress best known for her role as the quirky landlady Helen Roper on the television sitcom "Three's Company" and its spin-off "The Ropers."
-
E.
Laura Rister
Laura Rister is a film producer and executive known for her work on independent and prestige projects, including the financial thriller "Margin Call."
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156866de48190a744e8dcaa0c66f1 |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5b0833081909668c042234b5b75 |
completed | May 9, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69ffb6a526188190be80658fb23cacbd |
completed | May 9, 2026, 10:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb71cea948190a1c5998654aee8d5 |
completed | May 9, 2026, 10:37 p.m. |
Created at: April 10, 2026, 4:52 a.m.