Triple
T819548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret |
E17722
|
entity |
| Predicate | hasShortForm |
P43
|
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: [Margaret, hasShortForm, Rita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rita Context triple: [Margaret, hasShortForm, Rita]
-
A.
Rita
chosen
Rita is a feminine given name used in various cultures, often as a short form of names like Margarita.
-
B.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
C.
Linda
Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
-
D.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
-
E.
Sonia
Sonia is a central female character in the romantic comedy film "Think Like a Man," whose relationships and personal growth intersect with the movie’s ensemble cast and themes about modern dating.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab656418819091ecb09e7ede2825 |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2578477c8190983de0a1065ad8ec |
completed | March 7, 2026, 1:17 p.m. |
Created at: March 1, 2026, 7:38 p.m.