Triple
T9669251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of God |
E233983
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object |
Ed Cortês
Ed Cortês is a Brazilian composer best known for his film scores, particularly his work on acclaimed Brazilian cinema.
|
E813221
|
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: Ed Cortês | Statement: [City of God, musicBy, Ed Cortês]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ed Cortês Context triple: [City of God, musicBy, Ed Cortês]
-
A.
Mark Vicente
Mark Vicente is a cinematographer and filmmaker best known for his work on the documentary "What the Bleep Do We Know!?" and his involvement in the NXIVM organization.
-
B.
Brian VanDeMark
Brian VanDeMark is an American historian and author known for his work on U.S. foreign policy and the Vietnam War, including coauthoring influential studies of that conflict.
-
C.
Adrian Cronauer
Adrian Cronauer was a real-life U.S. Air Force radio DJ during the Vietnam War whose irreverent broadcasting style inspired the character portrayed by Robin Williams in the film "Good Morning, Vietnam."
-
D.
Jon Caliri
Jon Caliri is an actor best known for playing the character Vinnie Pasetta.
-
E.
Ray Nazarro
Ray Nazarro was an American film director best known for his prolific work on low-budget Westerns and action films during the 1940s and 1950s.
- 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: Ed Cortês Triple: [City of God, musicBy, Ed Cortês]
Generated description
Ed Cortês is a Brazilian composer best known for his film scores, particularly his work on acclaimed Brazilian cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ed Cortês Target entity description: Ed Cortês is a Brazilian composer best known for his film scores, particularly his work on acclaimed Brazilian cinema.
-
A.
Mark Vicente
Mark Vicente is a cinematographer and filmmaker best known for his work on the documentary "What the Bleep Do We Know!?" and his involvement in the NXIVM organization.
-
B.
Brian VanDeMark
Brian VanDeMark is an American historian and author known for his work on U.S. foreign policy and the Vietnam War, including coauthoring influential studies of that conflict.
-
C.
Adrian Cronauer
Adrian Cronauer was a real-life U.S. Air Force radio DJ during the Vietnam War whose irreverent broadcasting style inspired the character portrayed by Robin Williams in the film "Good Morning, Vietnam."
-
D.
Jon Caliri
Jon Caliri is an actor best known for playing the character Vinnie Pasetta.
-
E.
Ray Nazarro
Ray Nazarro was an American film director best known for his prolific work on low-budget Westerns and action films during the 1940s and 1950s.
- 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_69ca848f55e48190b3f67252571c3d45 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c3d5b3481908c8c66a3528875aa |
completed | April 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18a247ca48190910624dfbf0b491d |
completed | April 4, 2026, 10:01 p.m. |
| NEDg | Description generation | batch_69d18acf86588190bc000f701bcaaa1c |
completed | April 4, 2026, 10:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d18ba396cc8190a3ded2ac3968c553 |
completed | April 4, 2026, 10:07 p.m. |
Created at: March 30, 2026, 8:15 p.m.