Triple
T4791887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Engel de Ruyter |
E106620
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Engel |
E385482
|
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: Engel | Statement: [Engel de Ruyter, givenName, Engel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Engel Context triple: [Engel de Ruyter, givenName, Engel]
-
A.
Engel
chosen
Engel is a German-origin surname borne by numerous notable individuals across fields such as science, politics, and the arts.
-
B.
Enger
Enger is a small historic town in North Rhine-Westphalia, Germany, traditionally associated with the medieval County of Ravensberg and the legendary Saxon leader Widukind.
-
C.
Eitel
Eitel is the introspective, spiritually searching protagonist of Norman Mailer’s novel "The Deer Park."
-
D.
Erich
Erich is a masculine given name of German origin, commonly used in German-speaking countries and beyond.
-
E.
Eberl
Eberl is a German-language surname of Austrian and Bavarian origin borne by various notable individuals.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65ddff388190b55071ed5cae7688 |
completed | March 20, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43ecf0308190941809fd13efa393 |
completed | March 21, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:22 p.m.