Triple

T11156733
Position Surface form Disambiguated ID Type / Status
Subject Mia Dolan E263928 entity
Predicate notableLocation P3858 FINISHED
Object Mount Hollywood E97468 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: Mount Hollywood | Statement: [Mia Dolan, notableLocation, Mount Hollywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Hollywood
Context triple: [Mia Dolan, notableLocation, Mount Hollywood]
  • A. Mount Hollywood chosen
    Mount Hollywood is a prominent peak in Los Angeles’ Griffith Park offering panoramic views of the city and the surrounding hills.
  • B. Tubbs Hill
    Tubbs Hill is a popular natural area and hiking destination on the shores of Lake Coeur d'Alene in Idaho, known for its scenic trails, forested terrain, and waterfront views.
  • C. Moran Hill
    Moran Hill is a prominent scenic hill and historic park area in central Pyongyang, North Korea, known for its cultural monuments, pavilions, and views over the city.
  • D. Tower Hill
    Tower Hill is a nearby settlement to Kirkby in England, likely a small village or locality within the surrounding rural area.
  • E. Tower Hill
    Tower Hill is a strategically significant elevation that served as a key defensive position during the World War II Battle of Tannenberg Line in Estonia.
  • 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_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8741cd48190b7cc29c6b6bc54ff completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e46352e0688190924f15bc7d7ede90 completed April 19, 2026, 5:08 a.m.
Created at: April 8, 2026, 9:28 p.m.