Triple
T20308702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Wakefield |
E510175
|
entity |
| Predicate | hasBodyOfWater |
P1778
|
FINISHED |
| Object | Crystal Lake |
—
|
NE NERFINISHED |
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: Crystal Lake | Statement: [Town of Wakefield, hasBodyOfWater, Crystal Lake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crystal Lake Context triple: [Town of Wakefield, hasBodyOfWater, Crystal Lake]
-
A.
Crystal Lake
Crystal Lake is a large, clear, and popular recreational inland lake in northwestern Michigan known for its scenic beauty and outdoor activities.
-
B.
Crystal Lake
Crystal Lake is a small freshwater lake located in the town of Sand Lake in upstate New York.
-
C.
Crystal Lake
Crystal Lake is a recreational lake in Burnsville, Minnesota, known for activities such as boating, fishing, and swimming.
-
D.
Crystal Lake
Crystal Lake is the fictional, ill-fated lakeside setting of the Friday the 13th horror film series, notorious as the stalking grounds of killer Jason Voorhees.
-
E.
Crystal Lake
chosen
Crystal Lake is a small freshwater lake and public recreation area located in Wakefield, Massachusetts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c7491c8190961113c4283b10b0 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6774286a88190800d6b062f3d7a9f |
completed | April 20, 2026, 6:58 p.m. |
Created at: April 16, 2026, 11:18 a.m.