Triple
T9548823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melanie Lynskey |
E230366
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Melanie |
E490528
|
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 | Statement: [Melanie Lynskey, givenName, Melanie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melanie Context triple: [Melanie Lynskey, 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 the given first name of British actress Thandiwe Newton, who was previously credited professionally as Thandie Newton.
-
C.
Melanie
chosen
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)."
-
D.
Melanie Mills
Melanie Mills is known as the spouse of former professional American football center Sam Mills.
-
E.
Melanie Miller
Melanie Miller is a film and television producer known for her work on projects such as the documentary "Navalny."
- 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99059138819088ae54b26df979cf |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c82c98c8190a4fd6fc3ceb4173d |
completed | April 4, 2026, 5:38 p.m. |
Created at: March 30, 2026, 8:02 p.m.