Triple
T22259427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Godmothered |
E550177
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Eleanor |
—
|
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: Eleanor | Statement: [Godmothered, character, Eleanor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eleanor Context triple: [Godmothered, character, Eleanor]
-
A.
Eleanor
Eleanor is a feminine given name most famously borne by Eleanor Roosevelt, the influential First Lady of the United States and human rights advocate.
-
B.
Eleanor
Eleanor was one of the merchant ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest against British taxation in 1773.
-
C.
Eleanor
Eleanor is the daughter of American model and actress Devon Aoki.
-
D.
Eleanor
Eleanor is a compassionate caretaker and ally in the adventure drama film "The Peanut Butter Falcon," where she helps guide and protect the protagonists on their journey.
-
E.
Eleanor
chosen
Eleanor is the optimistic, inexperienced fairy godmother-in-training who stars as the protagonist of the Disney fantasy comedy film "Godmothered."
- 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c5b54c8190854690ba599639fa |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.