Triple

T20945952
Position Surface form Disambiguated ID Type / Status
Subject Mamilla Alrov Center E515843 entity
Predicate adjacentTo P224 FINISHED
Object Mamilla Cemetery NE NERFINISHED

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: Mamilla Cemetery | Statement: [Mamilla Alrov Center, adjacentTo, Mamilla Cemetery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mamilla Cemetery
Context triple: [Mamilla Alrov Center, adjacentTo, Mamilla Cemetery]
  • A. Mamilla Cemetery chosen
    Mamilla Cemetery is an ancient Islamic burial ground in Jerusalem, historically significant for its centuries-old tombs and its location near the Old City.
  • B. Prazeres Cemetery
    Prazeres Cemetery is a historic and monumental cemetery in Lisbon, Portugal, known for its elaborate mausoleums and as the resting place of many notable Portuguese figures.
  • C. Jellaz Cemetery
    Jellaz Cemetery is a historic and prominent Muslim burial ground in Tunis, Tunisia, known as the resting place of many notable Tunisian figures.
  • D. Mai Dich Cemetery
    Mai Dich Cemetery is a prominent national cemetery in Hanoi, Vietnam, where many high-ranking Communist Party and state leaders are buried.
  • E. Anif Cemetery
    Anif Cemetery is the local burial ground serving the municipality of Anif in the Salzburg region of Austria.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4fcd678819087a304291f14330a completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fad7f67481908675e76736f5e0c3 completed April 21, 2026, 4:19 a.m.
Created at: April 16, 2026, 12:56 p.m.