Triple
T13766947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl Humann |
E330773
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Essen, Germany |
E311580
|
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: Essen, Germany | Statement: [Carl Humann, placeOfBirth, Essen, Germany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Essen, Germany Context triple: [Carl Humann, placeOfBirth, Essen, Germany]
-
A.
Essen
chosen
Essen is a major industrial and cultural city in western Germany, historically known as a coal and steel center and now home to several large corporations and universities.
-
B.
Hamm, Germany
Hamm is a city in the German state of North Rhine-Westphalia, known as an industrial and transportation hub in the eastern Ruhr area.
-
C.
Brühl, Germany
Brühl, Germany is a town in North Rhine-Westphalia known for its UNESCO-listed Augustusburg and Falkenlust palaces and its proximity to Cologne.
-
D.
Frankfort, Germany
Frankfort, Germany is a German city whose name has been used for places abroad, including the village of Frankfort in Illinois, USA.
-
E.
Friedberg, Germany
Friedberg, Germany is a historic town in the state of Hesse known for its medieval architecture, including a well-preserved castle and old town center.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0227f2c48190983ccc9395e4e7a2 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0724ab481908448d71a1bd02253 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:10 p.m.