Triple
T3661974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rita R. Colwell |
E77669
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Rita |
E12279
|
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: Rita | Statement: [Rita R. Colwell, hasGivenName, Rita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rita Context triple: [Rita R. Colwell, hasGivenName, Rita]
-
A.
Rita
chosen
Rita is a feminine given name used in various cultures, often as a short form of names like Margarita.
-
B.
Rita Gam
Rita Gam was an American film and television actress known for her work in the 1950s and 1960s, including roles in films such as "The Thief" and "King of Kings."
-
C.
Lillita
Lillita is the birth name of Lita Grey, the American actress best known for her early silent film work and marriage to Charlie Chaplin.
-
D.
Raisa
Raisa Gorbacheva was the influential and highly visible wife of Soviet leader Mikhail Gorbachev, known for her intellectual background, public role, and charitable work.
-
E.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d826d88190b0b50e8592088a36 |
completed | March 8, 2026, 6:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48846af9881909d71d63b8bd8d141 |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.