Triple
T14184715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Bundesbank headquarters |
E351543
|
entity |
| Predicate | cityDistrict |
P2709
|
FINISHED |
| Object | Bockenheim |
E129394
|
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: Bockenheim | Statement: [Deutsche Bundesbank headquarters, cityDistrict, Bockenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bockenheim Context triple: [Deutsche Bundesbank headquarters, cityDistrict, Bockenheim]
-
A.
Bockenheim
chosen
Bockenheim is a lively urban district of Frankfurt am Main known for its mix of residential areas, shops, and university facilities.
-
B.
Stadelhofen
Stadelhofen is a village and district of the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
C.
Frankfurt (Main) Süd
Frankfurt (Main) Süd is a major railway station in Frankfurt am Main, Germany, serving regional, S-Bahn, and long-distance trains south of the city center.
-
D.
Stuttgart-Süd
Stuttgart-Süd is a central urban district of Stuttgart, Germany, known for its historic residential areas, hillside views, and vibrant cultural and nightlife scene.
-
E.
Stuttgart-Vaihingen
Stuttgart-Vaihingen is a district in the southwest of Stuttgart, Germany, known as a residential and business area with important transport links and educational institutions.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61cc0a848190b660095972b1223b |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd280656a881909c565b99e85ae9bd |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:03 a.m.