Triple
T5989706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Park Cities |
E133313
|
entity |
| Predicate | hasPark |
P105
|
FINISHED |
| Object | Lakeside Park |
E351662
|
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: Lakeside Park | Statement: [Park Cities, hasPark, Lakeside Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakeside Park Context triple: [Park Cities, hasPark, Lakeside Park]
-
A.
Lakeside Park
chosen
Lakeside Park is a public recreational park in Pawling, New York, known for its lakeside setting and outdoor activities.
-
B.
Lakeshore Park
Lakeshore Park is a large recreational park in Novi, Michigan, known for its wooded trails, beach on Walled Lake, and family-friendly outdoor amenities.
-
C.
Silver Lake Park
Silver Lake Park is a public recreational area in Middletown, Delaware, featuring a lake, open green spaces, and outdoor amenities for community use.
-
D.
Silver Lake Park
Silver Lake Park is a local recreational area in Croton-on-Hudson, New York, known for its lakeside setting and outdoor activities.
-
E.
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.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc76fd481908cc3f327e532a1a6 |
completed | March 22, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7421871888190aab99c6c5f6c147d |
completed | March 28, 2026, 2:51 a.m. |
Created at: March 22, 2026, 4:05 p.m.