Triple
T2141548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaan Einasto |
E46770
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jaan |
E227690
|
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: Jaan | Statement: [Jaan Einasto, givenName, Jaan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jaan Context triple: [Jaan Einasto, givenName, Jaan]
-
A.
Jaan
chosen
Jaan is a masculine given name commonly used in Estonia, equivalent to the English name John.
-
B.
Johan
Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
-
C.
Johanna
Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
-
D.
Aloysya
Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
-
E.
Toomas
Toomas is a masculine given name commonly used in Estonia and other Baltic and Nordic countries, equivalent to the English name Thomas.
- 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbe0543108190862dd9a4a861c758 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae51b37ce08190add9df46cc17ba89 |
completed | March 9, 2026, 4:50 a.m. |
Created at: March 4, 2026, 7:44 p.m.