Triple

T9749564
Position Surface form Disambiguated ID Type / Status
Subject MSV Duisburg E236404 entity
Predicate league P888 FINISHED
Object 3. Liga E185628 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: 3. Liga | Statement: [MSV Duisburg, league, 3. Liga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 3. Liga
Context triple: [MSV Duisburg, league, 3. Liga]
  • A. 3. Liga chosen
    3. Liga is the third tier of professional football in Germany, sitting below the Bundesliga and 2. Bundesliga in the national league system.
  • B. 2. Liga
    2. Liga is the common shorthand name for Germany’s second-tier professional football league, officially known as the 2. Bundesliga.
  • C. II liga
    II liga is the third tier of the Polish football league system, featuring professional and semi-professional clubs competing below the I liga and Ekstraklasa.
  • D. Liga II
    Liga II is the second tier of the Romanian professional football league system, sitting directly below Liga I.
  • E. Czech 2. Liga
    Czech 2. Liga is the second-highest professional football league in the Czech Republic, sitting directly below the Czech First League in the national league system.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f6a2f8c8190a6f6af6587ee90b8 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1b01678f88190900a941b9d111c58 completed April 5, 2026, 12:43 a.m.
Created at: March 30, 2026, 8:24 p.m.