Triple
T18117172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jess Wasikowska |
E433635
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Jess |
—
|
NE NERFINISHED |
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: Jess | Statement: [Jess Wasikowska, hasGivenName, Jess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jess Context triple: [Jess Wasikowska, hasGivenName, Jess]
-
A.
Jess
Jess is a supporting character in the romantic comedy film "When Harry Met Sally..." who serves as Harry’s best friend and provides comic relief and relationship advice.
-
B.
Jess
Jess is an 1887 adventure novel by H. Rider Haggard, set in South Africa and centered on romance, conflict, and colonial-era intrigue.
-
C.
Jess
chosen
Jess is the affectionate nickname commonly used for the character Jessica Day.
-
D.
Jessy
Jessy is a feminine given name commonly used in English-speaking countries, often as a variant of Jessie or Jessica.
-
E.
Jessika
Jessika is a feminine given name, typically considered a modern or alternative spelling of Jessica.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd67a2481909d27a4a49b095f8c |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.