Triple
T5649391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elly Heuss-Knapp |
E124464
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Straßburg |
E12607
|
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: Straßburg | Statement: [Elly Heuss-Knapp, placeOfBirth, Straßburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Straßburg Context triple: [Elly Heuss-Knapp, placeOfBirth, Straßburg]
-
A.
Strasbourg
chosen
Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
-
B.
Mulhouse
Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
-
C.
Wissembourg
Wissembourg is a historic town in northeastern France’s Alsace region, known for its well-preserved medieval architecture and proximity to the German border.
-
D.
Speyer
Speyer is a historic city in southwestern Germany on the Rhine River, renowned for its Romanesque imperial cathedral, a UNESCO World Heritage Site.
-
E.
Saarbrücken
Saarbrücken is a German city on the Saar River known as an industrial, cultural, and educational center near the French border.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d2ed648190a5152c8668cbda02 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097d395fc8190be9020d1fdbc9936 |
completed | March 23, 2026, 1:30 a.m. |
Created at: March 22, 2026, 3:42 p.m.