Triple
T19927787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mel Jones |
E478971
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Coraline Jones |
—
|
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: Coraline Jones | Statement: [Mel Jones, relative, Coraline Jones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coraline Jones Context triple: [Mel Jones, relative, Coraline Jones]
-
A.
Coraline Jones
chosen
Coraline Jones is the brave and curious young heroine of Neil Gaiman’s dark fantasy novella and its film adaptation, who discovers a sinister parallel world behind a secret door in her new home.
-
B.
Coralie
Coralie is a beautiful young actress in Honoré de Balzac’s novel "Lost Illusions," known for her tragic love affair with the ambitious poet Lucien de Rubempré.
-
C.
Coraline
Coraline is a dark fantasy novella by Neil Gaiman about a young girl who discovers a sinister parallel world behind a secret door in her new home.
-
D.
Lucy
Lucy, better known by her nickname Wyldstyle, is a rebellious and resourceful Master Builder from The Lego Movie franchise.
-
E.
Lucy
Lucy is a NASA Discovery Program space mission designed to study Jupiter’s Trojan asteroids to better understand the early solar system’s formation and evolution.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659cc1a448190aa98d4a66022457e |
completed | April 20, 2026, 4:52 p.m. |
Created at: April 10, 2026, 1:53 p.m.