Triple

T3913824
Position Surface form Disambiguated ID Type / Status
Subject The Treasure of the Sierra Madre E88786 entity
Predicate setInCity P7747 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: [The Treasure of the Sierra Madre, setInCity, Tampico]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tampico
Context triple: [The Treasure of the Sierra Madre, setInCity, 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. Matamoros
    Matamoros is a Mexican border city in the state of Tamaulipas, located directly across the Rio Grande from Brownsville, Texas, and known as an important hub for trade and manufacturing.
  • E. Manzanillo
    Manzanillo is a major Pacific coastal city in western Mexico known for its busy commercial port and popular beach tourism.
  • 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_69aed955229881909e85e73ffab1d343 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed38e2808190acbd0a7a3b677798 completed March 9, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5285c52808190b9cbb2e3e03a18cb completed March 14, 2026, 9:20 a.m.
Created at: March 9, 2026, 3:22 p.m.