Triple
T4559907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Woman |
E120566
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Steve Nolan
Steve Nolan is a fictional character appearing in the 1977 film "American Woman."
|
E452275
|
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: Steve Nolan | Statement: [American Woman, hasCharacter, Steve Nolan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Nolan Context triple: [American Woman, hasCharacter, Steve Nolan]
-
A.
David Nolan
David Nolan is a relatively common personal name shared by multiple individuals, including politicians, athletes, and fictional characters.
-
B.
Ken Nolan
Ken Nolan is an American screenwriter best known for adapting Mark Bowden’s nonfiction book into the acclaimed war film "Black Hawk Down."
-
C.
William Nolan
William Nolan is an editor known for his work on editions of classic adventure literature, including "The Mark of Zorro."
-
D.
Kevin Nolan
Kevin Nolan is an English former professional footballer best known as a goal-scoring midfielder for clubs such as Bolton Wanderers, Newcastle United, and West Ham United.
-
E.
Jeff Nelson
Jeff Nelson is a Major League Baseball umpire who has served in numerous postseason games, including as a crew chief in the World Series.
- 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: Steve Nolan Triple: [American Woman, hasCharacter, Steve Nolan]
Generated description
Steve Nolan is a fictional character appearing in the 1977 film "American Woman."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Steve Nolan Target entity description: Steve Nolan is a fictional character appearing in the 1977 film "American Woman."
-
A.
David Nolan
David Nolan is a relatively common personal name shared by multiple individuals, including politicians, athletes, and fictional characters.
-
B.
Ken Nolan
Ken Nolan is an American screenwriter best known for adapting Mark Bowden’s nonfiction book into the acclaimed war film "Black Hawk Down."
-
C.
William Nolan
William Nolan is an editor known for his work on editions of classic adventure literature, including "The Mark of Zorro."
-
D.
Kevin Nolan
Kevin Nolan is an English former professional footballer best known as a goal-scoring midfielder for clubs such as Bolton Wanderers, Newcastle United, and West Ham United.
-
E.
Jeff Nelson
Jeff Nelson is a Major League Baseball umpire who has served in numerous postseason games, including as a crew chief in the World Series.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd582b871c8190be0b70c76d639000 |
completed | March 20, 2026, 2:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdc593eaf881908a9043366230b391 |
completed | March 20, 2026, 10:09 p.m. |
| NEDg | Description generation | batch_69bdc5f0b52c8190bbfa2a6a22d56725 |
completed | March 20, 2026, 10:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdc63b1e0881908f861f7c9c5ce3ac |
completed | March 20, 2026, 10:12 p.m. |
Created at: March 20, 2026, 1:09 p.m.