Triple

T5420093
Position Surface form Disambiguated ID Type / Status
Subject Peter Debye E121226 entity
Predicate familyName P18 FINISHED
Object Debije
Debije is the Dutch spelling of the surname of Peter Debye, the Nobel Prize–winning physical chemist known for his work in molecular structure and dipole moments.
 E518982 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: Debije | Statement: [Peter Debye, familyName, Debije]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Debije
Context triple: [Peter Debye, familyName, Debije]
  • A. Debar
    Debar is a small town in western North Macedonia known for its proximity to Mount Korab and the Macedonian–Albanian border.
  • B. Bodbe
    Bodbe is a historic monastic complex and pilgrimage site in eastern Georgia, renowned as the burial place of Saint Nino, the evangelizer of the Georgian people.
  • C. Jérica
    Jérica is a historic municipality in the province of Castellón, in Spain’s Valencian Community, known for its medieval architecture and prominent Mudejar-style bell tower.
  • D. Kandıra
    Kandıra is a coastal town and district in northwestern Turkey known for its Black Sea beaches and rural landscapes within Kocaeli Province.
  • E. Sagarejo
    Sagarejo is a town in eastern Georgia that serves as an important local center in the Kakheti wine-producing region.
  • 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: Debije
Triple: [Peter Debye, familyName, Debije]
Generated description
Debije is the Dutch spelling of the surname of Peter Debye, the Nobel Prize–winning physical chemist known for his work in molecular structure and dipole moments.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Debije
Target entity description: Debije is the Dutch spelling of the surname of Peter Debye, the Nobel Prize–winning physical chemist known for his work in molecular structure and dipole moments.
  • A. Debar
    Debar is a small town in western North Macedonia known for its proximity to Mount Korab and the Macedonian–Albanian border.
  • B. Bodbe
    Bodbe is a historic monastic complex and pilgrimage site in eastern Georgia, renowned as the burial place of Saint Nino, the evangelizer of the Georgian people.
  • C. Jérica
    Jérica is a historic municipality in the province of Castellón, in Spain’s Valencian Community, known for its medieval architecture and prominent Mudejar-style bell tower.
  • D. Kandıra
    Kandıra is a coastal town and district in northwestern Turkey known for its Black Sea beaches and rural landscapes within Kocaeli Province.
  • E. Sagarejo
    Sagarejo is a town in eastern Georgia that serves as an important local center in the Kakheti wine-producing region.
  • 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_69bd463b58d88190b258261573de9e91 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87e8f1cc81908b997f8a417697c0 completed March 20, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3ab4d32c8190958daefa8061a7f9 completed March 22, 2026, 12:41 a.m.
NEDg Description generation batch_69bf3b4ab72c81908a4a80681fbd3fba completed March 22, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_69bf3be530188190bde63a481013d24e completed March 22, 2026, 12:46 a.m.
Created at: March 20, 2026, 2:06 p.m.