Triple
T33288614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open Flair Festival |
E852252
|
entity |
| Predicate | localImpact |
P89454
|
FINISHED |
| Object | important event for Eschwege 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: important event for Eschwege tourism | Statement: [Open Flair Festival, localImpact, important event for Eschwege tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localImpact Context triple: [Open Flair Festival, localImpact, important event for Eschwege tourism]
-
A.
hasLocalImpact
chosen
Indicates that an entity produces effects or consequences within a specific local area or community.
-
B.
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.
-
C.
socialImpact
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
D.
humanImpact
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
E.
landscapeImpact
Indicates how an action, project, or entity alters or affects the visual and physical character of a landscape.
- 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_69f349660ff48190a4568803d0b89941 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: May 1, 2026, 1:32 a.m.