Triple
T4284723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claire |
E97238
|
entity |
| Predicate | variant |
P4680
|
FINISHED |
| Object | Clara |
E94446
|
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: Clara | Statement: [Claire, variant, Clara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clara Context triple: [Claire, variant, Clara]
-
A.
Clara
chosen
Clara is a feminine given name of Latin origin, derived from "clarus" meaning "bright" or "famous."
-
B.
Clara
Clara is a character in the American folk opera "Porgy and Bess," known as a young mother whose lullaby "Summertime" is one of the work’s most famous songs.
-
C.
Lucile
Lucile is a popular 1860 verse novel by British writer Edward Bulwer-Lytton, known for its romantic plot and melodramatic style.
-
D.
Lucile
Lucile is a feminine given name of Latin origin, commonly associated with the name Lucille and meaning "light."
-
E.
Clara Weiss
Clara Weiss is a relatively obscure individual whose specific public achievements or biographical details are not widely documented.
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3503c062c81908f9a9eeab5381ec9 |
completed | March 12, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7c2023c8190a2359f8cabcecd2c |
completed | March 14, 2026, 7:32 p.m. |
Created at: March 12, 2026, 11:07 p.m.