Triple
T20632473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Burger |
E506990
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Peter |
—
|
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: Peter | Statement: [Peter Burger, hasGivenName, Peter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Context triple: [Peter Burger, hasGivenName, Peter]
-
A.
Peter
chosen
Peter is a common male given name of Greek origin, widely used in many languages and cultures, often associated with the meaning "rock" or "stone."
-
B.
Peter
Peter is the sensible and responsible leader of Enid Blyton’s Secret Seven children’s detective club.
-
C.
Peter
Peter was one of the leaders of the late 12th-century Bulgarian uprising that restored the Bulgarian Empire against Byzantine rule.
-
D.
Peter
Peter is the central protagonist in the British black comedy film "Death at a Funeral," around whom the chaotic and farcical events of the story unfold.
-
E.
Peter
Peter is a central character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s newsroom staff.
- 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad0bdcd88190a59d68e03370b271 |
completed | April 20, 2026, 10:47 p.m. |
Created at: April 16, 2026, 11:42 a.m.