Triple
T13864481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Ehrlich |
E333285
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Ehrlich |
E78710
|
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: Ehrlich | Statement: [Walter Ehrlich, hasFamilyName, Ehrlich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ehrlich Context triple: [Walter Ehrlich, hasFamilyName, Ehrlich]
-
A.
Ehrlich
chosen
Ehrlich is a German-origin surname borne by numerous notable individuals across fields such as science, medicine, and the arts.
-
B.
Lobenstein
Lobenstein is a historic town in present-day Thuringia, Germany, known for having served as the capital of one of the former Reuss principalities.
-
C.
Erwin
Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
-
D.
Ernst
Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
-
E.
Rattenberg
Rattenberg is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany, known for its rural setting and traditional Bavarian character.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de05c30d9c81908217d41a3b4aaf85 |
completed | April 14, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c10113288190b799126d934df92a |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:14 p.m.