Triple
T140757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikola Tesla |
E2843
|
entity |
| Predicate | hasUnitNamedAfter |
P63
|
FINISHED |
| Object | tesla (magnetic flux density unit) |
—
|
LITERAL 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: tesla (magnetic flux density unit) | Statement: [Nikola Tesla, hasUnitNamedAfter, tesla (magnetic flux density unit)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnitNamedAfter Context triple: [Nikola Tesla, hasUnitNamedAfter, tesla (magnetic flux density unit)]
-
A.
namedAfter
chosen
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
B.
historicallyRecognizedAs
Indicates that an entity has been acknowledged or designated under a particular name, status, or role during a past historical period.
-
C.
historicallyBorneBy
Indicates that an entity has carried, possessed, or used another entity (such as a name, title, or symbol) at some point in the past.
-
D.
hasNameOrigin
Indicates that the origin or source of an entity’s name is specified by the related entity.
-
E.
hasLatinName
Indicates that an entity is associated with a specific Latin (scientific) name.
- F. None of above.
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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565559ac81909e0c4e095a7dfa27 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.