Triple

T6155123
Position Surface form Disambiguated ID Type / Status
Subject Christian Matthias Theodor Mommsen E137300 entity
Predicate placeOfBirth P1 FINISHED
Object Garding E130980 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: Garding | Statement: [Christian Matthias Theodor Mommsen, placeOfBirth, Garding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garding
Context triple: [Christian Matthias Theodor Mommsen, placeOfBirth, Garding]
  • A. Garding chosen
    Garding is a small town in the Nordfriesland district of Schleswig-Holstein in northern Germany.
  • B. Garde
    Garde is the surname of American stage, film, and radio actress Betty Garde, known for her character roles in mid-20th-century entertainment.
  • C. Gardish
    Gardish is a 1993 Hindi action-drama film directed by Priyadarshan, known for Dimple Kapadia’s acclaimed performance alongside Jackie Shroff.
  • D. Gardez
    Gardez is a city in eastern Afghanistan that serves as the capital of Paktia Province and an important regional administrative and commercial center.
  • E. Gardon
    The Gardon is a river in southern France known for flowing through the Gard department and beneath the famous Pont du Gard Roman aqueduct.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c008a45d008190832a9e19f5d63406 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05d01ddb0819085b5f5338b86a25d completed March 22, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1418195d8819092743f323430b9a8 completed March 23, 2026, 1:34 p.m.
Created at: March 22, 2026, 4:17 p.m.