Triple
T506966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reinhard Heydrich |
E10522
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Halle an der Saale |
E94413
|
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: Halle an der Saale | Statement: [Reinhard Heydrich, placeOfBirth, Halle an der Saale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halle an der Saale Context triple: [Reinhard Heydrich, placeOfBirth, Halle an der Saale]
-
A.
Halle (Saale)
chosen
Halle (Saale) is a major city in the German state of Saxony-Anhalt, known as an important economic, cultural, and educational center, including being home to the Martin Luther University of Halle-Wittenberg.
-
B.
Jena
Jena is a historic university city in the German state of Thuringia, known for its role in optics, philosophy, and science.
-
C.
Hildesheim
Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
-
D.
Leipzig
Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
-
E.
Braunschweig
Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f14c83f08190b1028f4929866db4 |
completed | Feb. 28, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b830bf5c81908784e8146987eb96 |
completed | March 4, 2026, 4:42 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.