Triple
T851232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pink Line |
E18388
|
entity |
| Predicate | loopStation |
P15892
|
FINISHED |
| Object | State/Lake |
E86833
|
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: State/Lake | Statement: [Pink Line, loopStation, State/Lake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: State/Lake Context triple: [Pink Line, loopStation, State/Lake]
-
A.
Lake
chosen
Lake is a Chicago Transit Authority 'L' station in the Loop that serves the Red Line subway.
-
B.
Karen State
Karen State is a mountainous, ethnically diverse region in southeastern Myanmar known for its long-running conflict between Karen ethnic groups and the central government.
-
C.
STATE
STATE is the commonly used abbreviation for the United States Department of State, the federal executive department responsible for U.S. foreign policy and international relations.
-
D.
Grand Canyon State
The Grand Canyon State is the nickname of Arizona, highlighting its famous natural wonder, the Grand Canyon.
-
E.
Wisconsin
Wisconsin is a U.S. state in the Upper Midwest known for its dairy industry, Great Lakes shorelines, and mix of rural landscapes and industrial cities.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b66c908190a52f731119b77a1e |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a792a0666c8190bfc9166d45b4e867 |
completed | March 4, 2026, 2:02 a.m. |
Created at: March 1, 2026, 7:38 p.m.