Triple
T2285237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiffany |
E51374
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Tiffy |
E261012
|
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: Tiffy | Statement: [Tiffany, hasDiminutive, Tiffy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiffy Context triple: [Tiffany, hasDiminutive, Tiffy]
-
A.
Tiffy
chosen
Tiffy is a common nickname or diminutive form of the given name Tiffany.
-
B.
Tiffani
Tiffani is a given name, typically a modern variant of the name Tiffany used for girls.
-
C.
Liddy
Liddy is a surname most notably associated with G. Gordon Liddy, the former FBI agent and key figure in the Watergate scandal.
-
D.
Tina
Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
-
E.
Tina
Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc245dd208190b13c5f5d05aa6990 |
completed | March 7, 2026, 6:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3b974d881909b35dfd08def7b80 |
completed | March 9, 2026, 11:49 a.m. |
Created at: March 4, 2026, 7:48 p.m.