Triple
T16138436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica |
E391589
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Jesica |
E1199793
|
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: Jesica | Statement: [Jessica, hasVariant, Jesica]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jesica Context triple: [Jessica, hasVariant, Jesica]
-
A.
Jessika
chosen
Jessika is a feminine given name, typically considered a modern or alternative spelling of Jessica.
-
B.
Jenna
Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
-
C.
Julianna
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
-
D.
Nicole
Nicole is a feminine given name of Greek origin meaning "victory of the people," commonly used in many English- and French-speaking countries.
-
E.
Nicole
Nicole is a central character in the dark comedy-drama film "Hesher," serving as a key emotional anchor in the story’s exploration of grief and unconventional relationships.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a06e0988190b5cd62d422d058a2 |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0007833960819088334e10258a9d72 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:01 a.m.