Triple
T17390624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thandie Newton |
E422811
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Melanie |
—
|
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: Melanie | Statement: [Thandie Newton, givenName, Melanie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melanie Context triple: [Thandie Newton, givenName, Melanie]
-
A.
Melanie
Melanie is a supporting character in the comedy film "Grumpy Old Men," involved in the small-town relationships and humorous conflicts that drive the story.
-
B.
Melanie
Melanie is a feminine given name commonly used in various countries and languages.
-
C.
Melanie
chosen
Melanie is the given first name of British actress Thandiwe Newton, who was previously credited professionally as Thandie Newton.
-
D.
Melanie
Melanie is an American folk-pop singer-songwriter best known for her soulful vocals and 1970s hits like "Brand New Key" and "Lay Down (Candles in the Rain)."
-
E.
Melanie
Melanie is a character in Simon Gray's stage play "Quartermaine's Terms," which explores the personal lives and quiet tragedies of teachers at a 1960s Cambridge language school.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43ab950d4819098d6a46f67c46191 |
completed | April 19, 2026, 2:15 a.m. |
Created at: April 10, 2026, 5:45 a.m.