Triple
T2223860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emil Sieg |
E48602
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Emil |
E22883
|
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: Emil | Statement: [Emil Sieg, givenName, Emil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emil Context triple: [Emil Sieg, givenName, Emil]
-
A.
Emil
chosen
Emil is the given name of Carl Gustaf Emil Mannerheim, the renowned Finnish military leader and statesman who served as President of Finland.
-
B.
Oskar
Oskar is a masculine given name of Germanic origin, commonly used in various European countries.
-
C.
Alois
Alois is a masculine given name of Germanic origin, notably borne by Alois Hitler, the father of Adolf Hitler.
-
D.
Emilis
Emilis is a given name, primarily used in Lithuanian and other Baltic or Eastern European contexts, derived from the name Emil.
-
E.
Hans
Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03d1df88190950c691a4c246bd1 |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6afe4d1481908c6c27e889303892 |
completed | March 9, 2026, 6:38 a.m. |
Created at: March 4, 2026, 7:47 p.m.