Triple
T3168917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Rains Came |
E66278
|
entity |
| Predicate | costumeDesignBy |
P184
|
FINISHED |
| Object |
Royer
Royer was a costume designer known for his work on classic Hollywood films, including the 1939 drama "The Rains Came."
|
E333715
|
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: Royer | Statement: [The Rains Came, costumeDesignBy, Royer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Royer Context triple: [The Rains Came, costumeDesignBy, Royer]
-
A.
Delarue
Delarue is a vengeful ex-soldier and gunslinger who serves as the main protagonist in the Western thriller film "The Salvation."
-
B.
Mennekes
Mennekes is a German electrical engineering company best known in e-mobility for developing the widely adopted Type 2 AC charging connector for electric vehicles.
-
C.
Vivant Denon
Vivant Denon was a French diplomat, writer, artist, and pioneering museum director best known for helping to create and lead the Louvre Museum after the French Revolution.
-
D.
Lusser
Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
-
E.
Franck
Franck is a surname most notably associated with James Franck, the German physicist and Nobel laureate recognized for the Franck–Hertz experiment.
- 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: Royer Triple: [The Rains Came, costumeDesignBy, Royer]
Generated description
Royer was a costume designer known for his work on classic Hollywood films, including the 1939 drama "The Rains Came."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Royer Target entity description: Royer was a costume designer known for his work on classic Hollywood films, including the 1939 drama "The Rains Came."
-
A.
Delarue
Delarue is a vengeful ex-soldier and gunslinger who serves as the main protagonist in the Western thriller film "The Salvation."
-
B.
Mennekes
Mennekes is a German electrical engineering company best known in e-mobility for developing the widely adopted Type 2 AC charging connector for electric vehicles.
-
C.
Vivant Denon
Vivant Denon was a French diplomat, writer, artist, and pioneering museum director best known for helping to create and lead the Louvre Museum after the French Revolution.
-
D.
Lusser
Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
-
E.
Franck
Franck is a surname most notably associated with James Franck, the German physicist and Nobel laureate recognized for the Franck–Hertz experiment.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada64726048190933dbdc44258703e |
completed | March 8, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235e5a0e081909a03f5eb222cfe60 |
completed | March 12, 2026, 3:41 a.m. |
| NEDg | Description generation | batch_69b236962ee48190b37836e5fe6dbc37 |
completed | March 12, 2026, 3:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2373ebca88190b50735839eab4944 |
completed | March 12, 2026, 3:47 a.m. |
Created at: March 8, 2026, 3:06 p.m.