Triple

T14238108
Position Surface form Disambiguated ID Type / Status
Subject June Christy E352938 entity
Predicate notableSong P4 FINISHED
Object Tampico E81128 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: Tampico | Statement: [June Christy, notableSong, Tampico]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tampico
Context triple: [June Christy, notableSong, Tampico]
  • A. Tampico
    Tampico is a small village in Illinois best known as the birthplace of U.S. President Ronald Reagan.
  • B. Tampico, Mexico chosen
    Tampico, Mexico is a major port city on the Gulf of Mexico in the state of Tamaulipas, known historically for its oil industry and commercial significance.
  • C. Port of Veracruz
    The Port of Veracruz is one of Mexico’s oldest and most important seaports, serving as a key hub for international trade on the Gulf of Mexico.
  • D. Minatitlán
    Minatitlán is an industrial city in the Mexican state of Veracruz, known for its major oil refinery and strategic location in the petroleum industry.
  • E. Minatitlán
    Minatitlán is a small inland municipality in the Mexican state of Colima, known for its rural character and agricultural activities.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de62422e28819089e7115052a28c96 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c2bbfec81909ade3dd4306d69e3 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:08 a.m.