Triple

T37908747
Position Surface form Disambiguated ID Type / Status
Subject Christian Lindner E945628 entity
Predicate positionHeld P8 FINISHED
Object Leader of the Free Democratic Party
The Leader of the Free Democratic Party is the head of Germany’s liberal FDP, responsible for shaping its political agenda, public profile, and electoral strategy.
E2248137 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: Leader of the Free Democratic Party | Statement: [Christian Lindner, positionHeld, Leader of the Free Democratic Party]
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: Leader of the Free Democratic Party
Triple: [Christian Lindner, positionHeld, Leader of the Free Democratic Party]
Generated description
The Leader of the Free Democratic Party is the head of Germany’s liberal FDP, responsible for shaping its political agenda, public profile, and electoral strategy.

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_69f76ef20bb0819088b5b6ceecb0b8fc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd5c6c9881908821a7a70ad84bfd completed May 6, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a410cca9ea481909fb3b2065f6a35b3 completed June 28, 2026, noon
NEDg Description generation batch_6a410d5215e88190b53f93c0bfc61bfd completed June 28, 2026, 12:02 p.m.
NED2 Entity disambiguation (via description) batch_6a410e09a0d48190aae6deab051064a3 completed June 28, 2026, 12:05 p.m.
Created at: May 3, 2026, 4:20 p.m.