Triple
T18536487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turtle River Falls and Gardens |
E452977
|
entity |
| Predicate | supportsLocalEconomy |
P11337
|
FINISHED |
| Object | tourism |
—
|
LITERAL 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: tourism | Statement: [Turtle River Falls and Gardens, supportsLocalEconomy, tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsLocalEconomy Context triple: [Turtle River Falls and Gardens, supportsLocalEconomy, tourism]
-
A.
localEconomyImpact
Indicates the effect that an action, event, or entity has on the economic conditions, activities, or performance of a specific local area or community.
-
B.
usesLocalProduce
Indicates that one entity obtains and incorporates agricultural products sourced from nearby or locally based producers.
-
C.
localSponsor
Indicates that an entity provides sponsorship or support within a specific local area or community.
-
D.
hasLocalSupport
Indicates that an entity receives backing, endorsement, or assistance from people or organizations within its immediate geographic or community area.
-
E.
supportsCommunity
chosen
Indicates that one entity provides assistance, resources, or encouragement that benefits a community or group.
- F. None of above.
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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5340256d08190bf22d2cb064413b2 |
completed | April 19, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:37 a.m.