Triple

T16482416
Position Surface form Disambiguated ID Type / Status
Subject Heidiland E400352 entity
Predicate hasAttraction P105 FINISHED
Object Tamins E1216985 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: Tamins | Statement: [Heidiland, hasAttraction, Tamins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamins
Context triple: [Heidiland, hasAttraction, Tamins]
  • A. Tamins chosen
    Tamins is a municipality in the canton of Graubünden in eastern Switzerland, known for its location near the confluence of the Rhine rivers and its scenic Alpine surroundings.
  • B. Tarama
    Tarama is a small island municipality in Okinawa Prefecture, Japan, known for its subtropical climate, traditional Ryukyuan culture, and surrounding coral reefs.
  • C. Tumasik
    Tumasik is an old name for the island of Singapore, historically referenced in regional Malay and Javanese sources.
  • D. Talmis
    Talmis was an important ancient Nubian city that served as a major political and religious center for the Blemmyes in Lower Nubia.
  • E. Tepiman
    Tepiman is a subgroup of Uto-Aztecan languages spoken primarily in the southwestern United States and northern Mexico, including languages such as O'odham and Tepehuán.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e03643881908b16ddb9004af5d0 completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00607aafa48190929250a879c602ca completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 5:13 a.m.