Triple
T1319731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ballon d'Or |
E28188
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | golden ball |
E23485
|
NE FINISHED |
How this triple was built (2 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: golden ball | Statement: [Ballon d'Or, namedAfter, golden ball]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: golden ball Context triple: [Ballon d'Or, namedAfter, golden ball]
-
A.
Golden Ball
chosen
The Golden Ball is the award presented to the best player of the FIFA Club World Cup tournament.
-
B.
The Ball
The Ball is the popular nickname for Reunion Tower, a distinctive geodesic observation tower and Dallas landmark known for its glowing spherical top.
-
C.
Golden Pan
The Golden Pan is a prestigious literary award recognizing authors whose books have achieved significant commercial success, often marked by high sales milestones.
-
D.
Winner's Circle
Winner's Circle is the high-stakes final round of the game show "The $100,000 Pyramid," where contestants attempt to guess categories to win the top prize.
-
E.
Bola
Bola is the given name of Bola Tinubu, a prominent Nigerian politician and current president of Nigeria.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a498532c3481909223b74af2e578df |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c179883c8190b68fbeebb9696982 |
completed | March 1, 2026, 10:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbaf6a6d08190b8a30c2c64f15f59 |
completed | March 7, 2026, 11:55 p.m. |
Created at: March 1, 2026, 7:55 p.m.