Triple
T539983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strasbourg |
E12607
|
entity |
| Predicate | hasFestival |
P3113
|
FINISHED |
| Object | Strasbourg Christmas market |
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: Strasbourg Christmas market | Statement: [Strasbourg, hasFestival, Strasbourg Christmas market]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Strasbourg Christmas market Context triple: [Strasbourg, hasFestival, Strasbourg Christmas market]
-
A.
Grüner Markt
Grüner Markt is a central marketplace and public square in the Bavarian city of Fürth, known for its local vendors and historic urban setting.
-
B.
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.
-
C.
Colmar
Colmar is a picturesque historic town in northeastern France’s Alsace region, renowned for its well-preserved medieval and early Renaissance architecture and canals.
-
D.
Mondorf-les-Bains
Mondorf-les-Bains is a spa town in southeastern Luxembourg renowned for its thermal baths, wellness facilities, and casino.
-
E.
Sélestat
Sélestat is a historic town in the Alsace region of northeastern France, known for its well-preserved medieval architecture and cultural heritage.
- 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4c671eaac8190a4bc731a02a5b0e8 |
completed | March 1, 2026, 11:06 p.m. |
Created at: March 1, 2026, 7:32 p.m.