Triple
T769308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikola Tesla Museum |
E16244
|
entity |
| Predicate | hasCollection |
P426
|
FINISHED |
| Object | Nikola Tesla urn with ashes |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: Nikola Tesla urn with ashes | Statement: [Nikola Tesla Museum, hasCollection, Nikola Tesla urn with ashes]
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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a70376988190be2826259f5281ab |
completed | March 1, 2026, 8:52 p.m. |
Created at: March 1, 2026, 7:37 p.m.