Triple

T2759730
Position Surface form Disambiguated ID Type / Status
Subject Line 5 (Santiago Metro) E61190 entity
Predicate connectsDistrict P2564 FINISHED
Object Maipú E184706 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: Maipú | Statement: [Line 5 (Santiago Metro), connectsDistrict, Maipú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maipú
Context triple: [Line 5 (Santiago Metro), connectsDistrict, Maipú]
  • A. Maipú chosen
    Maipú is a populous commune and suburb of Santiago, Chile, known for its residential areas, commercial activity, and historical significance in the Santiago Metropolitan Region.
  • B. Maipú
    Maipú is a renowned wine-producing region in Argentina’s Mendoza Province, noted for its high-quality Malbec and other varietals.
  • C. Talcahuano
    Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
  • D. Rancagua
    Rancagua is a major Chilean city known for its mining industry and historical significance in the country’s independence, serving as an important commercial and administrative center south of Santiago.
  • E. La Serena
    La Serena is a coastal city in northern Chile known for its colonial architecture, beaches, and role as a gateway to major astronomical observatories in the region.
  • 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_69ab4b7bab6c8190a5c2efef19a8ef34 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd2121548190b96f174e6f61f9b5 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b276bd909c8190a227ae7af6f41547 completed March 12, 2026, 8:18 a.m.
Created at: March 6, 2026, 9:57 p.m.