Triple
T20268643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gary |
E499032
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Gazza |
—
|
NE NERFINISHED |
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: Gazza | Statement: [Gary, hasDiminutive, Gazza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gazza Context triple: [Gary, hasDiminutive, Gazza]
-
A.
Gazza
chosen
Gazza is a common British nickname, most famously associated with former England footballer Paul Gascoigne.
-
B.
Giggs
Giggs is a British rapper and songwriter from London known for his deep voice and influential role in the UK rap and grime scenes.
-
C.
Gakpe
Gakpe is another name for King Ghezo, the 19th-century ruler of the Kingdom of Dahomey in West Africa.
-
D.
Gerrard
Gerrard is a surname most notably associated with individuals such as Australian musician and composer Lisa Gerrard.
-
E.
Figo
Figo is a retired Portuguese footballer widely regarded as one of the greatest wingers of his generation, known for starring at clubs like Barcelona, Real Madrid, and Inter Milan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e675dbb7ac8190a40c527f2c02ca50 |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 11, 2026, 11:42 p.m.