Triple
T881517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tompkins County |
E19035
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Lansing |
E173950
|
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: [Tompkins County, hasTown, Lansing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lansing Context triple: [Tompkins County, hasTown, Lansing]
-
A.
Lansing
chosen
Lansing is a small village located within Tompkins County in central New York State, near the city of Ithaca.
-
B.
Lansing, Michigan
Lansing, Michigan is the capital city of the U.S. state of Michigan and a historic center of automobile manufacturing and industry.
-
C.
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.
-
D.
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.
-
E.
East Lansing
East Lansing is a city in central Michigan best known as the home of Michigan State University.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4accc863c8190be9e5350732c30b1 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad307c46988190bb4ba823ad313a88 |
completed | March 8, 2026, 8:17 a.m. |
Created at: March 1, 2026, 7:39 p.m.