Triple
T5734940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evan |
E126478
|
entity |
| Predicate | etymologicallyRelatedTo |
P5801
|
FINISHED |
| Object | John |
unclear NED1
|
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: John | Statement: [Evan, etymologicallyRelatedTo, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [Evan, etymologicallyRelatedTo, John]
-
A.
John
John is the given name of John Arbuthnot Fisher, a prominent British admiral and naval reformer of the late 19th and early 20th centuries.
-
B.
John
John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
-
C.
John
John is the given name of John Adams, the prominent American minimalist and post-minimalist composer known for works like "Nixon in China" and "Short Ride in a Fast Machine."
-
D.
John
John is the given first name of American character actor and comedian Rags Ragland.
-
E.
John
John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02536706c8190a69665b75c8a38e9 |
completed | March 22, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07ddd0f248190a796055212284542 |
completed | March 22, 2026, 11:40 p.m. |
Created at: March 22, 2026, 3:47 p.m.