Triple
T19891960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Borzage |
E478052
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Bad Girl
"Bad Girl" is a 1931 American pre-Code romantic drama film, directed by Frank Borzage and acclaimed for its realistic portrayal of working-class marriage and its Academy Award–winning achievements.
|
E1400552
|
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: Bad Girl | Statement: [Frank Borzage, notableWork, Bad Girl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Girl Context triple: [Frank Borzage, notableWork, Bad Girl]
-
A.
Bad Girl
"Bad Girl" is a high-energy R&B/pop single by Danity Kane known for its club-ready production and confident, empowering lyrics.
-
B.
Bad Girl
"Bad Girl" is a track from the album "Erotica," known for its provocative themes and sensual style.
-
C.
Little Bad Girl
"Little Bad Girl" is a dance-pop and electro house single by French DJ and producer David Guetta, featuring Taio Cruz and Ludacris.
-
D.
Good Girl
"Good Girl" is an uptempo country-pop song by Carrie Underwood that warns a woman about an untrustworthy lover, showcasing her powerful vocals and crossover appeal.
-
E.
Good Girl
Good Girl is a film featuring actress Vanessa Marquez in a significant role.
- 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: Bad Girl Triple: [Frank Borzage, notableWork, Bad Girl]
Generated description
"Bad Girl" is a 1931 American pre-Code romantic drama film, directed by Frank Borzage and acclaimed for its realistic portrayal of working-class marriage and its Academy Award–winning achievements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Girl Target entity description: "Bad Girl" is a 1931 American pre-Code romantic drama film, directed by Frank Borzage and acclaimed for its realistic portrayal of working-class marriage and its Academy Award–winning achievements.
-
A.
Bad Girl
"Bad Girl" is a high-energy R&B/pop single by Danity Kane known for its club-ready production and confident, empowering lyrics.
-
B.
Bad Girl
"Bad Girl" is a track from the album "Erotica," known for its provocative themes and sensual style.
-
C.
Little Bad Girl
"Little Bad Girl" is a dance-pop and electro house single by French DJ and producer David Guetta, featuring Taio Cruz and Ludacris.
-
D.
Good Girl
"Good Girl" is an uptempo country-pop song by Carrie Underwood that warns a woman about an untrustworthy lover, showcasing her powerful vocals and crossover appeal.
-
E.
Good Girl
Good Girl is a film featuring actress Vanessa Marquez in a significant role.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6590ed7988190bc6b610d1f4fa194 |
completed | April 20, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07dbd5cb948190b1f2ce3d59114bce |
completed | May 16, 2026, 2:52 a.m. |
| NEDg | Description generation | batch_6a07dd2dd31c8190bf70aab957afbcf5 |
completed | May 16, 2026, 2:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07ddf82b8881908675230d8fbac101 |
completed | May 16, 2026, 3:01 a.m. |
Created at: April 10, 2026, 1:52 p.m.