Triple
T5597866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States state capitals |
E147041
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Lansing |
E16556
|
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: Lansing | Statement: [United States state capitals, hasPart, Lansing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lansing Context triple: [United States state capitals, hasPart, Lansing]
-
A.
Lansing
Lansing is a surname of English origin borne by various notable individuals, including American statesman Robert Lansing.
-
B.
Lansing
Lansing is a small village located within Tompkins County in central New York State, near the city of Ithaca.
-
C.
Lansing, Michigan
chosen
Lansing, Michigan is the capital city of the U.S. state of Michigan and a historic center of automobile manufacturing and industry.
-
D.
Kalamazoo
Kalamazoo is a mid-sized city in southwestern Michigan known for its historic downtown, educational institutions like Western Michigan University, and a legacy of manufacturing and craft beer.
-
E.
Saginaw
Saginaw is a city in central Michigan known for its industrial history, location along the Saginaw River, and role as a regional economic and cultural center.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020c126088190914ef7b575d800e4 |
completed | March 22, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0286eaa2881909cbb0bb20f4987fe |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:38 p.m.