Triple
T8995406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frieda Hughes |
E214893
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Frieda |
E736343
|
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: Frieda | Statement: [Frieda Hughes, givenName, Frieda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frieda Context triple: [Frieda Hughes, givenName, Frieda]
-
A.
Frieda
Frieda is a 1947 British drama film produced by Michael Balcon that explores post-World War II tensions and prejudice in England.
-
B.
Frieda
chosen
Frieda is a minor Peanuts character known for her naturally curly hair and prim personality, who appears alongside Charlie Brown and his friends.
-
C.
Freda
Freda is a feminine given name, often used in English-speaking countries and derived from names like Winifred or Frederica.
-
D.
Berta
Berta is a fictional character in Paulo Coelho’s novel "The Devil and Miss Prym," serving as one of the villagers whose life and choices reflect the book’s central moral and spiritual dilemmas.
-
E.
Berta
Berta is a Nilo-Saharan language spoken primarily in parts of Sudan and Ethiopia.
- 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_69ca83a05c608190bdfdbdb25e994b39 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc68ddff288190869731df2c178ff6 |
completed | April 1, 2026, 12:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0d0e6a08190a2faf4157b8a9cd4 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:04 p.m.