Triple
T14455755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delicacy |
E358454
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object | Nathalie Kerr |
E1112412
|
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: Nathalie Kerr | Statement: [Delicacy, hasMainCharacter, Nathalie Kerr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathalie Kerr Context triple: [Delicacy, hasMainCharacter, Nathalie Kerr]
-
A.
Nathalie Kerr
chosen
Nathalie Kerr is a fictional character from the work "Delicacy," likely serving as a key figure in its narrative.
-
B.
Jocelyn Ritchie
Jocelyn Ritchie is a musician best known for her collaborative work with American rock-rap artist Kid Rock.
-
C.
Nina Warren
Nina Warren was the wife of U.S. Chief Justice and former California Governor Earl Warren and a prominent political hostess and partner in his public life.
-
D.
Julie Yorn
Julie Yorn is an American film producer known for her work on a range of Hollywood movies, including comedies and thrillers.
-
E.
Jocelyn Lane
Jocelyn Lane is a British-born actress and model best known for her film roles in the 1950s and 1960s, including appearances in adventure and comedy movies.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91a9c0d48190ae015e5e0db806ca |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde163c3488190aac5a8bd769d5564 |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:19 a.m.