Triple
T325467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jem |
E6507
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Jimmy |
E24180
|
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: Jimmy | Statement: [Jem, hasSpellingVariant, Jimmy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jimmy Context triple: [Jem, hasSpellingVariant, Jimmy]
-
A.
Jack
Jack is a common masculine given name, often used as a familiar form of John and widely featured in English-language literature and popular culture.
-
B.
Jamie
Jamie is a given name commonly used as a diminutive or variant of James, and is borne by people of all genders in English-speaking countries.
-
C.
Jim
chosen
Jim is a common English given name, typically used as a diminutive or familiar form of James.
-
D.
Jimmy Ba
Jimmy Ba is a prominent machine learning researcher known for his work on deep learning optimization methods such as the Adam optimizer.
-
E.
Simon
Simon is the given name of Simon Bolivar Buckner Jr., a U.S. Army lieutenant general who was killed in action while commanding forces during the Battle of Okinawa in World War II.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea959f9c819084602b8a1b5e66dd |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a44cb342c08190bcdcdbecf6ba4244 |
completed | March 1, 2026, 2:26 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.