Triple
T7848160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waukesha County, Wisconsin |
E181970
|
entity |
| Predicate | hasPark |
P105
|
FINISHED |
| Object | Frame Park |
E693647
|
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: Frame Park | Statement: [Waukesha County, Wisconsin, hasPark, Frame Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frame Park Context triple: [Waukesha County, Wisconsin, hasPark, Frame Park]
-
A.
Frame Park
chosen
Frame Park is a popular riverside public park in Waukesha, Wisconsin, known for its scenic Fox River views, walking trails, and recreational amenities.
-
B.
Chain Park
Chain Park is a public recreational park located in Hattiesburg, Mississippi.
-
C.
Cellucci Park
Cellucci Park is a public recreational area located in the town of Hudson, Massachusetts.
-
D.
Tei Park
Tei Park is a public park located in Sector 2 of Bucharest, Romania, known for its green spaces and recreational areas.
-
E.
Banshee Boardwalk
Banshee Boardwalk is a dark, haunted pier-themed race course in Mario Kart 64 featuring narrow wooden paths, ghosts, and eerie atmosphere.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18e7f5988190808ae4dcfbc06991 |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5afbb02481909008eb295c4825c1 |
completed | March 31, 2026, 5:26 a.m. |
Created at: March 30, 2026, 4:49 p.m.