Triple
T76202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ET |
E1522
|
entity |
| Predicate | usedInCity |
P4810
|
FINISHED |
| Object | Detroit |
E2603
|
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: Detroit | Statement: [ET, usedInCity, Detroit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Detroit Context triple: [ET, usedInCity, Detroit]
-
A.
Detroit
chosen
Detroit is a major U.S. city in Michigan known historically as the center of the American automotive industry and for its influential contributions to music, particularly Motown.
-
B.
Jackson, Michigan
Jackson, Michigan is a mid-sized city in south-central Michigan historically notable as the birthplace of the Republican Party in the 1850s.
-
C.
Grand Rapids, Michigan
Grand Rapids, Michigan is a mid-sized city in western Michigan known for its strong Dutch-American heritage, vibrant arts scene, and historic furniture manufacturing industry.
-
D.
Flint, Michigan
Flint, Michigan is an industrial city in the United States best known as the birthplace of General Motors and for its central role in the American automotive industry.
-
E.
Lansing, Michigan
Lansing, Michigan is the capital city of the U.S. state of Michigan and a historic center of automobile manufacturing and industry.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2567c90308190a9b989c586f7e559 |
completed | Feb. 28, 2026, 2:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2bf646ce88190b7c48f66c786e6bd |
completed | Feb. 28, 2026, 10:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.