Triple
T1794788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Grass Harp |
E39578
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Verena Talbo |
E165554
|
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: Verena Talbo | Statement: [The Grass Harp, featuresCharacter, Verena Talbo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verena Talbo Context triple: [The Grass Harp, featuresCharacter, Verena Talbo]
-
A.
Verena
chosen
Verena is a feminine given name of Latin origin, commonly used in German-speaking and other European countries.
-
B.
Franziska
Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
-
C.
Dorothee
Dorothee is a feminine given name, commonly used in German- and French-speaking countries, that is a variant of the name Dorothea.
-
D.
Sophie von Haselberg
Sophie von Haselberg is an American actress and producer, known for her work in film, television, and theater as well as for being the daughter of entertainer Bette Midler and artist Martin von Haselberg.
-
E.
Cecilia Krull
Cecilia Krull is a Spanish singer best known for performing the iconic theme song "My Life Is Going On" from the television series Money Heist.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa653daa0c8190a5d96c20c8a0af15 |
completed | March 6, 2026, 5:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc9a799fc81909acb620f3e569265 |
completed | March 8, 2026, 7:10 p.m. |
Created at: March 4, 2026, 7:32 p.m.