Triple
T13571747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Dakota State University |
E324178
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Brookings |
E176539
|
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: Brookings | Statement: [South Dakota State University, city, Brookings]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brookings Context triple: [South Dakota State University, city, Brookings]
-
A.
Brookings
chosen
Brookings is a small city in eastern South Dakota known for being home to South Dakota State University and serving as a regional center for education and research.
-
B.
Brookings
Brookings is a small coastal city in southwestern Oregon known for its mild climate, scenic Pacific shoreline, and outdoor recreation opportunities.
-
C.
Berkelland
Berkelland is a municipality in the eastern Netherlands, located in the Achterhoek region of the province of Gelderland.
-
D.
Lanham
Lanham is an unincorporated community in Prince George's County, Maryland, located in the suburban Washington, D.C. metropolitan area.
-
E.
Burkley
Burkley is a surname most notably associated with American character actor Dennis Burkley.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0106cb48190b20eb9bda131a68a |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bb61a40819099a62f65a68dff7b |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.