Triple

T1764344
Position Surface form Disambiguated ID Type / Status
Subject Lichtenberg E38727 entity
Predicate contains P35 FINISHED
Object Alt-Lichtenberg locality
Alt-Lichtenberg locality is a neighborhood within the Berlin borough of Lichtenberg, known as part of the city's eastern residential and urban area.
 E196875 NE FINISHED

How this triple was built (4 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: Alt-Lichtenberg locality | Statement: [Lichtenberg, contains, Alt-Lichtenberg locality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alt-Lichtenberg locality
Context triple: [Lichtenberg, contains, Alt-Lichtenberg locality]
  • A. Alt-Mariendorf
    Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
  • B. Ennigerloh
    Ennigerloh is a small town in the German state of North Rhine-Westphalia, known as the birthplace of mathematician Karl Weierstrass.
  • C. Ronsdorf
    Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
  • D. Schöneberg
    Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
  • E. Boblingen
    Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Alt-Lichtenberg locality
Triple: [Lichtenberg, contains, Alt-Lichtenberg locality]
Generated description
Alt-Lichtenberg locality is a neighborhood within the Berlin borough of Lichtenberg, known as part of the city's eastern residential and urban area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alt-Lichtenberg locality
Target entity description: Alt-Lichtenberg locality is a neighborhood within the Berlin borough of Lichtenberg, known as part of the city's eastern residential and urban area.
  • A. Alt-Mariendorf
    Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
  • B. Ennigerloh
    Ennigerloh is a small town in the German state of North Rhine-Westphalia, known as the birthplace of mathematician Karl Weierstrass.
  • C. Ronsdorf
    Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
  • D. Schöneberg
    Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
  • E. Boblingen
    Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
  • F. None of above. chosen

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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa646665088190afa31bdf48f14316 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0f12fd8819099759ebcdfc19494 completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada1e424f88190b070f28789121458 completed March 8, 2026, 4:20 p.m.
NED2 Entity disambiguation (via description) batch_69ada298cc1081909faef3bdecbcbfd0 completed March 8, 2026, 4:23 p.m.
Created at: March 4, 2026, 7:31 p.m.