Triple
T15289406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Right (2015 film) |
E365487
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Martha McKay
Martha McKay is a fictional character in the 2015 romantic action-comedy film "Mr. Right."
|
E1366347
|
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: Martha McKay | Statement: [Mr. Right (2015 film), character, Martha McKay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martha McKay Context triple: [Mr. Right (2015 film), character, Martha McKay]
-
A.
Martha Dix
Martha Dix was the wife and frequent model of German painter Otto Dix, known from many of his portraits and family scenes.
-
B.
Marie McKay
Marie McKay was the wife of Austrian-American actor Joseph Schildkraut, a prominent performer of stage and early Hollywood cinema.
-
C.
Martha Pattridge
Martha Pattridge is known as the wife of longtime Manhattan District Attorney Robert M. Morgenthau.
-
D.
Martha Hudson
Martha Hudson is an American sprinter who was one of the top female track athletes of her era, notably competing internationally under coach Ed Temple at Tennessee State University.
-
E.
Martha Lindsay
Martha Lindsay is known primarily as the daughter of American actress and pianist Diana Lynn.
- 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: Martha McKay Triple: [Mr. Right (2015 film), character, Martha McKay]
Generated description
Martha McKay is a fictional character in the 2015 romantic action-comedy film "Mr. Right."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martha McKay Target entity description: Martha McKay is a fictional character in the 2015 romantic action-comedy film "Mr. Right."
-
A.
Martha Dix
Martha Dix was the wife and frequent model of German painter Otto Dix, known from many of his portraits and family scenes.
-
B.
Marie McKay
Marie McKay was the wife of Austrian-American actor Joseph Schildkraut, a prominent performer of stage and early Hollywood cinema.
-
C.
Martha Pattridge
Martha Pattridge is known as the wife of longtime Manhattan District Attorney Robert M. Morgenthau.
-
D.
Martha Hudson
Martha Hudson is an American sprinter who was one of the top female track athletes of her era, notably competing internationally under coach Ed Temple at Tennessee State University.
-
E.
Martha Lindsay
Martha Lindsay is known primarily as the daughter of American actress and pianist Diana Lynn.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00e5635b4819092a69b5806d15bff |
completed | April 15, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0705b8a3f481909c748d6ff6f27f64 |
completed | May 15, 2026, 11:38 a.m. |
| NEDg | Description generation | batch_6a0706e5cfe08190b1b2419c0eec15ff |
completed | May 15, 2026, 11:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a070763ca5c81908afa73b30645223a |
completed | May 15, 2026, 11:45 a.m. |
Created at: April 10, 2026, 3:15 a.m.