Triple
T3575934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexanderson alternator |
E75687
|
entity |
| Predicate | firstUseYear |
P24583
|
FINISHED |
| Object | circa 1906 |
—
|
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: circa 1906 | Statement: [Alexanderson alternator, firstUseYear, circa 1906]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstUseYear Context triple: [Alexanderson alternator, firstUseYear, circa 1906]
-
A.
firstProductionYear
Indicates the year in which something (such as a product, work, or item) was first produced.
-
B.
firstYearOfUse
chosen
Indicates the year in which something was first put into use or began being used.
-
C.
wasFirstBuiltInYear
Indicates that the initial construction of an entity was completed in a specified year.
-
D.
firstRunningYear
Indicates the year in which something (such as an event, service, or operation) first began running or was initially active.
-
E.
firstUsedOn
Indicates the date, time, or context in which something was initially applied, activated, or put into use on a particular object or entity.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0da77008190922f414b85b9cad4 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.