Triple
T2550355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intolerance |
E56609
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Mae Marsh |
E151737
|
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: Mae Marsh | Statement: [Intolerance, stars, Mae Marsh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mae Marsh Context triple: [Intolerance, stars, Mae Marsh]
-
A.
Mae Marsh
chosen
Mae Marsh was an American silent film actress best known for her emotionally powerful performances in early cinema, particularly in D.W. Griffith’s landmark films.
-
B.
Dorys Madden
Dorys Madden is best known as the wife of Basketball Hall of Famer Julius "Dr. J" Erving.
-
C.
Dorothy Marie Marsh
Dorothy Marie Marsh, better known as Dottie West, was an influential American country music singer-songwriter who helped shape the Nashville sound from the 1960s through the 1980s.
-
D.
Armina Marshall
Armina Marshall was an American theater producer and director best known as a co-founder and leading figure of the influential Theatre Guild on Broadway.
-
E.
Marjorie
Marjorie is a feminine given name of French origin that has been widely used in English-speaking countries.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2e930508190a6bc9fc4fa431070 |
completed | March 7, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5d114964819092b847c701a0704e |
completed | March 9, 2026, 11:51 p.m. |
Created at: March 6, 2026, 9:48 p.m.