Triple
T2408331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felix |
E50326
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Feli |
E50326
|
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: Feli | Statement: [Felix, hasDiminutive, Feli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Feli Context triple: [Felix, hasDiminutive, Feli]
-
A.
Felix
chosen
Felix is a masculine given name of Latin origin meaning "happy" or "fortunate," borne by numerous historical and contemporary figures.
-
B.
Fifi
Fifi was one of Jane Goodall’s most closely observed wild chimpanzees at Gombe, known for her long-term presence in the study and her role in revealing chimpanzee social and family dynamics.
-
C.
Kitty
Kitty is a common diminutive or nickname for the given name Catherine.
-
D.
Kitty
"Kitty" is a 1945 historical comedy-drama film set in 18th-century London, best known for starring Paulette Goddard as a pickpocket who rises in society.
-
E.
Mr. Goodkat
Mr. Goodkat is a mysterious, highly skilled hitman central to the plot of the crime thriller film "Lucky Number Slevin."
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc92408308190ad2d331ebee71d15 |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3eba9d08190a2c63e590e08b4df |
completed | March 9, 2026, 11:50 a.m. |
Created at: March 4, 2026, 7:58 p.m.