Triple

T3311230
Position Surface form Disambiguated ID Type / Status
Subject Olympic Green E69575 entity
Predicate transportConnection P1298 FINISHED
Object Olympic Sports Center station E337410 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: Olympic Sports Center station | Statement: [Olympic Green, transportConnection, Olympic Sports Center station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olympic Sports Center station
Context triple: [Olympic Green, transportConnection, Olympic Sports Center station]
  • A. Olympic Sports Center station chosen
    Olympic Sports Center station is a Beijing Subway station serving the Olympic Green area near major sports venues built for the 2008 Summer Olympics.
  • B. Innovation Center station
    Innovation Center station is a Washington Metro rail station in Virginia located near the Dulles Technology Corridor, serving the Silver Line.
  • C. Xicun Station
    Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
  • D. Jishuitan station
    Jishuitan station is a subway station in Beijing that serves the busy Line 2 loop near the city’s northern central area.
  • E. Songyuan Road Station
    Songyuan Road Station is a Shanghai Metro station located in the city's Changning District.
  • 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_69ad859f218081909458d2cebbf57565 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0ec80508190baa78435b983b7b5 completed March 8, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3f0d52081908bbade5e514f17d1 completed March 12, 2026, 5:12 p.m.
Created at: March 8, 2026, 3:11 p.m.