Triple

T10282577
Position Surface form Disambiguated ID Type / Status
Subject Til Schweiger E241140 entity
Predicate givenName P17 FINISHED
Object Til
Til is the first name of Til Schweiger, a prominent German actor, filmmaker, and producer known for his roles in both German cinema and international films.
 E852528 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: Til | Statement: [Til Schweiger, givenName, Til]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Til
Context triple: [Til Schweiger, givenName, Til]
  • A. Tiltil
    Tiltil is a small town and commune in central Chile known for its rural character and historical significance within the Santiago Metropolitan Region.
  • B. Tilpa
    Tilpa is a tiny, remote village on the Darling River in outback New South Wales, Australia, known for its historic pub and role as a stopover for travelers and river communities.
  • C. Tilakkam
    Tilakkam is a small island that forms part of the Kalpeni atoll in the Lakshadweep archipelago of India.
  • D. Tilok
    Tilok is a variant spelling of the Indian given name "Tilak," commonly used in South Asian cultures.
  • E. Tilottama
    Tilottama is a central fictional heroine in Bankim Chandra Chattopadhyay’s Bengali historical novel "Durgeshnandini," noted for her beauty, courage, and romantic storyline.
  • 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: Til
Triple: [Til Schweiger, givenName, Til]
Generated description
Til is the first name of Til Schweiger, a prominent German actor, filmmaker, and producer known for his roles in both German cinema and international films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Til
Target entity description: Til is the first name of Til Schweiger, a prominent German actor, filmmaker, and producer known for his roles in both German cinema and international films.
  • A. Tiltil
    Tiltil is a small town and commune in central Chile known for its rural character and historical significance within the Santiago Metropolitan Region.
  • B. Tilpa
    Tilpa is a tiny, remote village on the Darling River in outback New South Wales, Australia, known for its historic pub and role as a stopover for travelers and river communities.
  • C. Tilakkam
    Tilakkam is a small island that forms part of the Kalpeni atoll in the Lakshadweep archipelago of India.
  • D. Tilok
    Tilok is a variant spelling of the Indian given name "Tilak," commonly used in South Asian cultures.
  • E. Tilottama
    Tilottama is a central fictional heroine in Bankim Chandra Chattopadhyay’s Bengali historical novel "Durgeshnandini," noted for her beauty, courage, and romantic storyline.
  • 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_69d381a94c1881908fc38fc263d9b9c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2a22f9881908b220dbe1e80c101 completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f83c3c488190b728783bc260b006 completed April 9, 2026, 12:52 a.m.
NEDg Description generation batch_69d6fcae243c819095a2e791716805bd completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd3495fc8190a093d2536cfbe58a completed April 9, 2026, 1:13 a.m.
Created at: April 6, 2026, 11:39 a.m.