Triple

T27474849
Position Surface form Disambiguated ID Type / Status
Subject SC Freiburg E693427 entity
Predicate headCoach P256 FINISHED
Object Christian Streich
Christian Streich is a long-serving German football manager and former player, best known for his passionate touchline presence and successful development of SC Freiburg into a stable Bundesliga club.
E1975151 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: Christian Streich | Statement: [SC Freiburg, headCoach, Christian Streich]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Christian Streich
Triple: [SC Freiburg, headCoach, Christian Streich]
Generated description
Christian Streich is a long-serving German football manager and former player, best known for his passionate touchline presence and successful development of SC Freiburg into a stable Bundesliga club.

Provenance (5 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_69ef5381f2648190a2392d0fab833095 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62e43391481908de5e30f1ae077df completed May 2, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2b9448def48190b948c9f4dd6a0fa5 completed June 12, 2026, 5:08 a.m.
NEDg Description generation batch_6a2b950959f48190ad19907e9c9a64c6 completed June 12, 2026, 5:11 a.m.
NED2 Entity disambiguation (via description) batch_6a2b957d073081909a1657bd313ad8cd completed June 12, 2026, 5:13 a.m.
Created at: April 27, 2026, 12:56 p.m.