Triple
T10348245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | India Wilkes |
E243808
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | Melanie Hamilton |
E154125
|
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: Melanie Hamilton | Statement: [India Wilkes, supports, Melanie Hamilton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melanie Hamilton Context triple: [India Wilkes, supports, Melanie Hamilton]
-
A.
Melanie Hamilton
chosen
Melanie Hamilton is a gentle, selfless Southern woman in Margaret Mitchell's novel and the film "Gone with the Wind," known for her unwavering kindness, loyalty, and moral strength.
-
B.
Melanie Hancock
Melanie Hancock is known as the stepdaughter of acclaimed British actor John Thaw.
-
C.
Melanie Sorich
Melanie Sorich is the wife of American character actor Clint Howard.
-
D.
Melanie Mayron
Melanie Mayron is an American actress and director best known for her Emmy-winning role on the television series "thirtysomething" and her work behind the camera on numerous TV shows.
-
E.
Melanie Vogel
Melanie Vogel is a German politician and member of the Alliance 90/The Greens party who has served in the Bundesrat and is known for her work on education and social policy.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e945d51881908dd2af6c78344c9b |
completed | April 7, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89f53484881909fb976efb3882b9b |
completed | April 10, 2026, 6:57 a.m. |
Created at: April 6, 2026, 11:56 a.m.