Triple
T14358644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kissing Jessica Stein |
E356037
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Jessica Stein |
E520858
|
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: Jessica Stein | Statement: [Kissing Jessica Stein, character, Jessica Stein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jessica Stein Context triple: [Kissing Jessica Stein, character, Jessica Stein]
-
A.
Jessica Stein
chosen
Jessica Stein is a fictional New York journalist and the romantically conflicted protagonist of the 2001 indie romantic comedy film "Kissing Jessica Stein."
-
B.
Sarah Koskoff
Sarah Koskoff is an American actress and screenwriter known for her work in independent films and television.
-
C.
Alicia Marcus
Alicia Marcus is a key character in the Resident Evil film series, serving as the elderly founder of the Umbrella Corporation and the original human template for the Red Queen AI.
-
D.
Shana Stein
Shana Stein is a television producer best known for her executive production work on the crime drama series "Power Book II: Ghost."
-
E.
Ruby Goldstein
Ruby Goldstein was a prominent American boxing referee and former fighter known for officiating major bouts in the mid-20th century.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f52ca7881908704eef20228aed3 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c48dd408190ac45ad4ca6f610c3 |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:15 a.m.