Triple
T5930567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIFA Women's World Cup Trophy |
E131925
|
entity |
| Predicate | designedBy |
P184
|
FINISHED |
| Object |
William Sawaya
William Sawaya is an Italian designer best known in sports for creating the iconic FIFA Women's World Cup Trophy.
|
E556005
|
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: William Sawaya | Statement: [FIFA Women's World Cup Trophy, designedBy, William Sawaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Sawaya Context triple: [FIFA Women's World Cup Trophy, designedBy, William Sawaya]
-
A.
Gil Avérous
Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
-
B.
Richard Baratta
Richard Baratta is an American film producer and production manager known for his work on major Hollywood features and television projects.
-
C.
Gabriel Brener
Gabriel Brener is a businessman and investor best known in sports for his former ownership stake in Major League Soccer’s Houston Dynamo.
-
D.
David Sardy
David Sardy is an American record producer, composer, and musician known for his work with rock bands and on major film soundtracks.
-
E.
Michael Wandmacher
Michael Wandmacher is an American film and television composer known for his work on horror and action projects, including the score for "My Bloody Valentine 3D."
- 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: William Sawaya Triple: [FIFA Women's World Cup Trophy, designedBy, William Sawaya]
Generated description
William Sawaya is an Italian designer best known in sports for creating the iconic FIFA Women's World Cup Trophy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: William Sawaya Target entity description: William Sawaya is an Italian designer best known in sports for creating the iconic FIFA Women's World Cup Trophy.
-
A.
Gil Avérous
Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
-
B.
Richard Baratta
Richard Baratta is an American film producer and production manager known for his work on major Hollywood features and television projects.
-
C.
Gabriel Brener
Gabriel Brener is a businessman and investor best known in sports for his former ownership stake in Major League Soccer’s Houston Dynamo.
-
D.
David Sardy
David Sardy is an American record producer, composer, and musician known for his work with rock bands and on major film soundtracks.
-
E.
Michael Wandmacher
Michael Wandmacher is an American film and television composer known for his work on horror and action projects, including the score for "My Bloody Valentine 3D."
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0389c734081908e8a35f43e0104f6 |
completed | March 22, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c05eb4b8819097f203e1db94ae8f |
completed | March 23, 2026, 4:23 a.m. |
| NEDg | Description generation | batch_69c0c1db6d548190ba4be143aa7c7905 |
completed | March 23, 2026, 4:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0c2bdd44881909aa85589d31e771a |
completed | March 23, 2026, 4:34 a.m. |
Created at: March 22, 2026, 4 p.m.