Triple
T12522607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | This Way Please |
E299355
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Karl Tunberg |
E288330
|
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: Karl Tunberg | Statement: [This Way Please, screenwriter, Karl Tunberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karl Tunberg Context triple: [This Way Please, screenwriter, Karl Tunberg]
-
A.
Karl Tunberg
chosen
Karl Tunberg was an American screenwriter best known for writing the screenplay of the epic 1959 film "Ben-Hur."
-
B.
William Tunberg
William Tunberg was an American screenwriter best known for adapting the classic 1957 Disney film "Old Yeller."
-
C.
Carl Kjeldsberg
Carl Kjeldsberg is a pathologist and academic leader best known as a co-founder of ARUP Laboratories, a major national clinical and anatomic pathology reference laboratory.
-
D.
Karl Sodersten
Karl Sodersten is a film editor known for his work on the Australian psychological thriller "Lantana."
-
E.
Christian Lundeberg
Christian Lundeberg was a Swedish conservative politician who briefly served as Prime Minister of Sweden in 1905 during the dissolution of the union with Norway.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9545c2aa081908e8a5a94d30e23eb |
completed | April 10, 2026, 7:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bc159c88190835fea5c0d9ee799 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.