Triple
T3277039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Émile |
E68781
|
entity |
| Predicate | cognateWith |
P2525
|
FINISHED |
| Object | Emilis |
E126365
|
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: Emilis | Statement: [Émile, cognateWith, Emilis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emilis Context triple: [Émile, cognateWith, Emilis]
-
A.
Emilis
chosen
Emilis is a given name, primarily used in Lithuanian and other Baltic or Eastern European contexts, derived from the name Emil.
-
B.
Emil
Emil is the given name of Carl Gustaf Emil Mannerheim, the renowned Finnish military leader and statesman who served as President of Finland.
-
C.
Emilian
Emilian is a Gallo-Italic Romance language variety spoken primarily in the Emilia region of northern Italy.
-
D.
Mikelis
Mikelis is a given name, primarily used in Latvia, that serves as a local variant of the name Michael.
-
E.
Simas
Simas is a surname most notably associated with David Simas, an American lawyer and former political advisor who served in the Obama administration.
- 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0128f08819084644f3c8fda2596 |
completed | March 8, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3c764548190ac3c90da3763ac62 |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:10 p.m.