Triple
T15219404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shore Park |
E363723
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Shore Park |
E363723
|
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: Shore Park | Statement: [Shore Park, name, Shore Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shore Park Context triple: [Shore Park, name, Shore Park]
-
A.
Shore Park
chosen
Shore Park is a public recreational park located in Pelham, New York.
-
B.
Shoreline Park
Shoreline Park is a large waterfront recreational area in Mountain View, California, featuring trails, a lake, wildlife habitats, and scenic views of the San Francisco Bay.
-
C.
Shoreline Park
Shoreline Park is a popular coastal bluff-top park in Santa Barbara, California, known for its ocean views, walking paths, and beach access.
-
D.
Shoreline Park
Shoreline Park is a public recreational area in Gulf Breeze, Florida, known for its waterfront access, outdoor activities, and scenic natural surroundings.
-
E.
South Shore Park
South Shore Park is a public lakeside park in Milwaukee, Wisconsin, known for its scenic Lake Michigan shoreline, beach, and recreational amenities.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007709d3881908384f0fe1e0218d0 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed345d58c81908a8fd182c0fe7c15 |
completed | May 9, 2026, 6:25 a.m. |
Created at: April 10, 2026, 3:11 a.m.