Triple
T3702335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mackenzie Foy |
E80807
|
entity |
| Predicate | portrayed |
P1668
|
FINISHED |
| Object |
Jo Green
Jo Green is a fictional character played by actress Mackenzie Foy, best known from her role in the film "The Nutcracker and the Four Realms."
|
E381885
|
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: Jo Green | Statement: [Mackenzie Foy, portrayed, Jo Green]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jo Green Context triple: [Mackenzie Foy, portrayed, Jo Green]
-
A.
Jo Green
Jo Green is a British theatre administrator best known as the longtime wife of actor and comedian Hugh Laurie.
-
B.
Joan Templeman
Joan Templeman is the longtime partner and wife of British entrepreneur Sir Richard Branson, known for her low public profile despite her association with the Virgin Group founder.
-
C.
Renée Lees
Renée Lees was the wife of prominent British philosopher A. J. Ayer.
-
D.
Nina Warren
Nina Warren was the wife of U.S. Chief Justice and former California Governor Earl Warren and a prominent political hostess and partner in his public life.
-
E.
Melanie Ralston
Melanie Ralston is a laid-back, manipulative surfer girl and stoner who becomes entangled in the criminal schemes surrounding Ordell Robbie in Quentin Tarantino’s film "Jackie Brown."
- 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: Jo Green Triple: [Mackenzie Foy, portrayed, Jo Green]
Generated description
Jo Green is a fictional character played by actress Mackenzie Foy, best known from her role in the film "The Nutcracker and the Four Realms."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jo Green Target entity description: Jo Green is a fictional character played by actress Mackenzie Foy, best known from her role in the film "The Nutcracker and the Four Realms."
-
A.
Jo Green
Jo Green is a British theatre administrator best known as the longtime wife of actor and comedian Hugh Laurie.
-
B.
Joan Templeman
Joan Templeman is the longtime partner and wife of British entrepreneur Sir Richard Branson, known for her low public profile despite her association with the Virgin Group founder.
-
C.
Renée Lees
Renée Lees was the wife of prominent British philosopher A. J. Ayer.
-
D.
Nina Warren
Nina Warren was the wife of U.S. Chief Justice and former California Governor Earl Warren and a prominent political hostess and partner in his public life.
-
E.
Melanie Ralston
Melanie Ralston is a laid-back, manipulative surfer girl and stoner who becomes entangled in the criminal schemes surrounding Ordell Robbie in Quentin Tarantino’s film "Jackie Brown."
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54925b48190b23d2a14ef825abc |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4cdf53190819098529d11a5a3c7a8 |
completed | March 14, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69b4cf799ae88190bbf821f4c4500031 |
completed | March 14, 2026, 3:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4d0057fe8819092a40732324f88c9 |
completed | March 14, 2026, 3:03 a.m. |
Created at: March 8, 2026, 3:33 p.m.