Triple
T2815562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larry King |
E54273
|
entity |
| Predicate | changedSurnameFrom |
P33067
|
FINISHED |
| Object | Zeiger |
E54273
|
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: Zeiger | Statement: [Larry King, changedSurnameFrom, Zeiger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zeiger Context triple: [Larry King, changedSurnameFrom, Zeiger]
-
A.
Zeiger
chosen
Zeiger is the birth surname of famed American television and radio host Larry King.
-
B.
Gage
Gage is a surname of English origin borne by various notable individuals, including historical and contemporary figures.
-
C.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
D.
Diesel (licensed watches)
Diesel (licensed watches) is a fashion watch line known for its bold, oversized, and industrial-inspired designs, produced under license by Fossil Group for the Diesel lifestyle brand.
-
E.
Elster
Elster is a river in central Europe, primarily flowing through the German state of Saxony and its surrounding regions.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4ed4ac81909f1ec4a3f7869bc1 |
completed | March 7, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8aecd5081909b38d229904e5bde |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 9:59 p.m.