Triple
T17149414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skull Mountain |
E416178
|
entity |
| Predicate | parkSection |
P5641
|
FINISHED |
| Object | Lakefront |
E1252035
|
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: Lakefront | Statement: [Skull Mountain, parkSection, Lakefront]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakefront Context triple: [Skull Mountain, parkSection, Lakefront]
-
A.
Lakefront
chosen
Lakefront is a themed area within Six Flags Great Adventure that features attractions, rides, and amenities along the park’s waterfront.
-
B.
Lakefront Reservation
Lakefront Reservation is a Cleveland-area public parkland along the Lake Erie shoreline, offering beaches, trails, and recreational access to the waterfront.
-
C.
Portage Bay waterfront
Portage Bay waterfront is a scenic shoreline area along Portage Bay in Seattle, known for its views, houseboats, and proximity to the University of Washington.
-
D.
Naha waterfront
Naha waterfront is a coastal urban area in Naha, Okinawa, known for its port facilities, seaside promenades, and views over the East China Sea.
-
E.
Lakeside
Lakeside is an upscale seafood restaurant at the Wynn Las Vegas known for its lakefront views and fine dining experience.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f4059d90819092d3609326fa3130 |
completed | April 18, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0148337a348190b8739eb3f553f1d9 |
completed | May 11, 2026, 3:08 a.m. |
Created at: April 10, 2026, 5:36 a.m.