Triple

T9081365
Position Surface form Disambiguated ID Type / Status
Subject Tahoma Glacier E217632 entity
Predicate namedAfter P63 FINISHED
Object Tahoma
Tahoma is an alternative Indigenous-derived name for Mount Rainier, a prominent stratovolcano in Washington State, USA.
 E162107 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: Tahoma | Statement: [Tahoma Glacier, namedAfter, Tahoma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tahoma
Context triple: [Tahoma Glacier, namedAfter, Tahoma]
  • A. Tayasan
    Tayasan is a coastal municipality in the province of Negros Oriental in the Philippines, known for its rural communities and agricultural economy.
  • B. Typer
    Typer is a modern, user-friendly Python library for building command-line interfaces, created by Sebastián Ramírez (tiangolo), that emphasizes type hints and automatic documentation.
  • C. Turley
    Turley is an unincorporated community and census-designated place in northeastern Oklahoma, situated just north of Tulsa.
  • D. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • E. Tinée
    Tinée is a river in southeastern France that flows through the Alpes-Maritimes department in the Provence-Alpes-Côte d'Azur 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: Tahoma
Triple: [Tahoma Glacier, namedAfter, Tahoma]
Generated description
Tahoma is an alternative Indigenous-derived name for Mount Rainier, a prominent stratovolcano in Washington State, USA.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tahoma
Target entity description: Tahoma is an alternative Indigenous-derived name for Mount Rainier, a prominent stratovolcano in Washington State, USA.
  • A. Tahoma chosen
    Tahoma is the Indigenous name commonly used by local Native American tribes for Mount Rainier, a prominent stratovolcano in Washington State.
  • B. Tayasan
    Tayasan is a coastal municipality in the province of Negros Oriental in the Philippines, known for its rural communities and agricultural economy.
  • C. Typer
    Typer is a modern, user-friendly Python library for building command-line interfaces, created by Sebastián Ramírez (tiangolo), that emphasizes type hints and automatic documentation.
  • D. Turley
    Turley is an unincorporated community and census-designated place in northeastern Oklahoma, situated just north of Tulsa.
  • E. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • F. None of above.

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_69ca83d7a0388190ba1af89ed7ba36f9 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc9608a82481908918821884ba5796 completed April 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffe28ae548190924cc7bbf453f3f3 completed April 3, 2026, 5:51 p.m.
NEDg Description generation batch_69d000d4a4548190939a9a9946be469b completed April 3, 2026, 6:03 p.m.
NED2 Entity disambiguation (via description) batch_69d001b245f08190a8e5c53c570b20a0 completed April 3, 2026, 6:06 p.m.
Created at: March 30, 2026, 7:13 p.m.