Triple
T10592597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I, Tina |
E250028
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Kurt Loder |
E603507
|
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: Kurt Loder | Statement: [I, Tina, author, Kurt Loder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kurt Loder Context triple: [I, Tina, author, Kurt Loder]
-
A.
Kurt Loder
chosen
Kurt Loder is an American film critic, author, and longtime MTV News journalist best known for his influential coverage of music and pop culture.
-
B.
Kurt Back
Kurt Back was a social psychologist known for his collaborative research in social behavior and group dynamics, including work with Leon Festinger.
-
C.
Kurt Diebner
Kurt Diebner was a German physicist who played a leading organizational role in Nazi Germany’s nuclear energy project during World War II.
-
D.
Leo Klier
Leo Klier was an American professional basketball player and two-time All-American at Notre Dame who played in the early years of the Basketball Association of America (BAA).
-
E.
Karl Schaefer
Karl Schaefer is a television writer and producer best known for co-creating the zombie apocalypse series Z Nation and its Netflix prequel Black Summer.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5277da8048190add007ca0c37253e |
completed | April 7, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e37382a0bc81908938b3cbdf0528e0 |
completed | April 18, 2026, 12:05 p.m. |
Created at: April 6, 2026, 12:40 p.m.