Triple
T19501118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gretel |
E487902
|
entity |
| Predicate | etymologicallyRelatedTo |
P5801
|
FINISHED |
| Object | Margaret |
—
|
NE NERFINISHED |
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: Margaret | Statement: [Gretel, etymologicallyRelatedTo, Margaret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margaret Context triple: [Gretel, etymologicallyRelatedTo, Margaret]
-
A.
Margaret
chosen
Margaret is a feminine given name of Greek origin, traditionally associated with the meaning "pearl" and widely used in English-speaking countries.
-
B.
Margaret
Margaret is a 2011 American drama film written and directed by Kenneth Lonergan, known for its complex portrayal of grief and moral responsibility following a tragic bus accident in New York City.
-
C.
Margaret
Margaret is a character in the animated series "Adventure Time," known as Finn the Human's caring adoptive mother.
-
D.
Margaret
Margaret is a central character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of broadcast journalists in the 1980s.
-
E.
Margaret
Margaret is a character who appears in the animated television series "Exit 9B" from the show "Regular Show."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6350ce7cc819086d77bbd9cd52b53 |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.