Triple
T18600977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moon Over Broadway |
E454617
|
entity |
| Predicate | features |
P997
|
FINISHED |
| Object |
Kate Miller
Kate Miller is an actress known for appearing in the documentary film "Moon Over Broadway."
|
E1333510
|
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: Kate Miller | Statement: [Moon Over Broadway, features, Kate Miller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Miller Context triple: [Moon Over Broadway, features, Kate Miller]
-
A.
Kate Miller
Kate Miller is a central character in Brian De Palma’s 1980 thriller film "Dressed to Kill," whose mysterious and tragic storyline drives much of the film’s suspense.
-
B.
Katey Miller
Katey Miller is the idealistic American teenager and aspiring dancer who becomes the protagonist of the romantic dance film "Dirty Dancing: Havana Nights."
-
C.
Kat Miller
Kat Miller is a determined and empathetic homicide detective on the television series "Cold Case," known for reopening and solving long-unsolved crimes.
-
D.
Kellie Miller
Kellie Miller is one of the plaintiffs who challenged Tennessee’s ban on recognizing same-sex marriages in the federal court case Tanco v. Haslam.
-
E.
Lynsey Miller
Lynsey Miller is a British television director known for her work on high-profile drama series, including the crime drama "Deadwater Fell."
- 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: Kate Miller Triple: [Moon Over Broadway, features, Kate Miller]
Generated description
Kate Miller is an actress known for appearing in the documentary film "Moon Over Broadway."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kate Miller Target entity description: Kate Miller is an actress known for appearing in the documentary film "Moon Over Broadway."
-
A.
Kate Miller
Kate Miller is a central character in Brian De Palma’s 1980 thriller film "Dressed to Kill," whose mysterious and tragic storyline drives much of the film’s suspense.
-
B.
Katey Miller
Katey Miller is the idealistic American teenager and aspiring dancer who becomes the protagonist of the romantic dance film "Dirty Dancing: Havana Nights."
-
C.
Kat Miller
Kat Miller is a determined and empathetic homicide detective on the television series "Cold Case," known for reopening and solving long-unsolved crimes.
-
D.
Kellie Miller
Kellie Miller is one of the plaintiffs who challenged Tennessee’s ban on recognizing same-sex marriages in the federal court case Tanco v. Haslam.
-
E.
Lynsey Miller
Lynsey Miller is a British television director known for her work on high-profile drama series, including the crime drama "Deadwater Fell."
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5475112608190acacc5ac7a08c4a0 |
completed | April 19, 2026, 9:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a050381bacc81909f416e8b9910f046 |
completed | May 13, 2026, 11:04 p.m. |
| NEDg | Description generation | batch_6a0504ff8c6c8190a211b3f3e30229b4 |
completed | May 13, 2026, 11:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0505606bf88190afe635b2517d170b |
completed | May 13, 2026, 11:12 p.m. |
Created at: April 10, 2026, 11:45 a.m.