Triple
T11232102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIFA World Cup mascots series |
E265846
|
entity |
| Predicate | hasMascot |
P52
|
FINISHED |
| Object | Ato |
E133196
|
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: Ato | Statement: [FIFA World Cup mascots series, hasMascot, Ato]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ato Context triple: [FIFA World Cup mascots series, hasMascot, Ato]
-
A.
Ato
chosen
Ato is one of the futuristic, computer-generated "Spheriks" characters who served as an official mascot for the 2002 FIFA World Cup in South Korea and Japan.
-
B.
Ateso
Ateso is a Nilotic language spoken primarily by the Teso people of eastern Uganda and western Kenya.
-
C.
Aoto
Aoto is a neighborhood in Tokyo, Japan, located within Katsushika Ward and known as a residential and commercial area with convenient rail access.
-
D.
Aytos
Aytos is a small town in southeastern Bulgaria known as an administrative and economic center within Burgas Province.
-
E.
Ateste
Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9026e1c81909456ac946bbba972 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad49b5cc8190b99cb2cd8de72109 |
completed | April 19, 2026, 10:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.