Triple
T7354919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grumpy Old Men |
E169597
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
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.
|
E658650
|
NE FINISHED |
How this triple was built (4 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: [Grumpy Old Men, character, Melanie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melanie Context triple: [Grumpy Old Men, character, Melanie]
-
A.
Melanie
Melanie is the given first name of British actress Thandiwe Newton, who was previously credited professionally as Thandie Newton.
-
B.
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)."
-
C.
Melanie Miller
Melanie Miller is a film and television producer known for her work on projects such as the documentary "Navalny."
-
D.
Joanne
Joanne is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
-
E.
Stephanie Mills
Stephanie Mills is an American R&B and soul singer best known for her powerful vocals and hit songs like "Never Knew Love Like This Before."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Melanie Triple: [Grumpy Old Men, character, Melanie]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Melanie Target entity description: 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.
-
A.
Melanie
Melanie is the given first name of British actress Thandiwe Newton, who was previously credited professionally as Thandie Newton.
-
B.
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)."
-
C.
Melanie Miller
Melanie Miller is a film and television producer known for her work on projects such as the documentary "Navalny."
-
D.
Joanne
Joanne is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
-
E.
Stephanie Mills
Stephanie Mills is an American R&B and soul singer best known for her powerful vocals and hit songs like "Never Knew Love Like This Before."
- F. None of above. chosen
Provenance (5 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f10e71fc81909307ca39a61142d3 |
completed | March 27, 2026, 9:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7faa25960819084ecb6dbf9369ba5 |
completed | March 28, 2026, 3:58 p.m. |
| NEDg | Description generation | batch_69c7fc2c90488190bd3aa5bf72606723 |
completed | March 28, 2026, 4:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7fcb5f7f0819081e70f8809bb34ae |
completed | March 28, 2026, 4:07 p.m. |
Created at: March 27, 2026, 3:05 p.m.