Triple
T4536840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John-John |
E107426
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | John-John |
E107426
|
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: John-John | Statement: [John-John, nickname, John-John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John-John Context triple: [John-John, nickname, John-John]
-
A.
John-John
chosen
John-John is the childhood nickname of John F. Kennedy Jr., the son of U.S. President John F. Kennedy and First Lady Jacqueline Kennedy Onassis.
-
B.
Johnny
Johnny is a common English masculine given name, often used as a familiar or diminutive form of John.
-
C.
Jono
Jono is a casual diminutive or nickname commonly used for the given name Jonathan.
-
D.
Jay-Jay
Jay-Jay is the widely known nickname of Nigerian football legend Augustine Azuka Okocha, celebrated for his exceptional dribbling skills and creativity on the pitch.
-
E.
Johner
Johner is a wisecracking mercenary and crew member of the spaceship Betty in the science fiction horror film "Alien: Resurrection," portrayed by actor Ron Perlman.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b78b8481909d79131723d4be22 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdacf5858081909d38cad86d4014f2 |
completed | March 20, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:04 p.m.