Triple
T18866003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johanna Spyri |
E461438
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Heidi |
—
|
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: Heidi | Statement: [Johanna Spyri, notableWork, Heidi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heidi Context triple: [Johanna Spyri, notableWork, Heidi]
-
A.
Heidi
Heidi is a 2015 family drama film adaptation of Johanna Spyri’s classic Swiss children’s novel about an orphan girl growing up in the Alps.
-
B.
Heidi
Heidi is a 1968 made-for-television film adaptation of Johanna Spyri’s classic novel about an orphaned Swiss girl and her life in the Alps.
-
C.
Heidi
Heidi is the spouse of Bernard "Beanie" Campbell, about whom little public biographical information is widely documented.
-
D.
Heidi
chosen
Heidi is a classic 1881 children’s novel by Swiss author Johanna Spyri about an orphan girl growing up in the Swiss Alps, renowned for its themes of nature, innocence, and moral development.
-
E.
Heidi
Heidi is a play by American playwright Halley Feiffer, known for its darkly comic exploration of complex emotional and familial dynamics.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c2a5074481908941fcbb3b3eefa2 |
completed | April 20, 2026, 6:07 a.m. |
Created at: April 10, 2026, 11:57 a.m.