Triple
T341879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meryl Streep |
E6853
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Streep |
E6853
|
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: Streep | Statement: [Meryl Streep, familyName, Streep]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Streep Context triple: [Meryl Streep, familyName, Streep]
-
A.
Meryl Streep
chosen
Meryl Streep is an acclaimed American actress widely regarded as one of the greatest performers of her generation, known for her versatility and record number of Academy Award nominations.
-
B.
Katharine Hepburn
Katharine Hepburn was an iconic American actress renowned for her fiercely independent screen persona, sharp wit, and a record four Academy Awards for Best Actress during Hollywood’s Golden Age.
-
C.
Daniel Day-Lewis
Daniel Day-Lewis is a highly acclaimed British-Irish method actor renowned for his intense character immersion and record three Academy Awards for Best Actor.
-
D.
Audrey Hepburn
Audrey Hepburn was an iconic British actress and humanitarian, celebrated for her timeless style and roles in classic films such as "Breakfast at Tiffany's."
-
E.
Dianne Wiest
Dianne Wiest is an acclaimed American actress known for her versatile performances in film, television, and theater, including multiple award-winning supporting roles.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae611f88190955fbebe2b01835b |
completed | Feb. 28, 2026, 1:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3dd2ff66c8190a0e688e4f9baa5b4 |
completed | March 1, 2026, 6:31 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.