Triple

T27229553
Position Surface form Disambiguated ID Type / Status
Subject Tiedemann Glacier E682112 entity
Predicate namedAfter P63 FINISHED
Object Hermann Otto Tiedemann
Hermann Otto Tiedemann was a 19th-century surveyor and engineer known for his work in British Columbia, Canada, for which Tiedemann Glacier was named in his honor.
E1783049 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: Hermann Otto Tiedemann | Statement: [Tiedemann Glacier, namedAfter, Hermann Otto Tiedemann]
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: Hermann Otto Tiedemann
Triple: [Tiedemann Glacier, namedAfter, Hermann Otto Tiedemann]
Generated description
Hermann Otto Tiedemann was a 19th-century surveyor and engineer known for his work in British Columbia, Canada, for which Tiedemann Glacier was named in his honor.

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_69eefacdad7881908b7bca61c90a1a1e completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6264dfc888190b2e25b84e8232246 completed May 2, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12da6920388190a1fe5b06148966b7 completed May 24, 2026, 11 a.m.
NEDg Description generation batch_6a12db5d2878819094252a665596a86e completed May 24, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_6a12dbe4c9e4819084be4a4f5e3b58a6 completed May 24, 2026, 11:07 a.m.
Created at: April 27, 2026, 9:45 a.m.