Triple
T12655714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunn’s Falls Park |
E302275
|
entity |
| Predicate | hasTypeOfMill |
P106029
|
FINISHED |
| Object | water-powered grist mill |
—
|
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: water-powered grist mill | Statement: [Dunn’s Falls Park, hasTypeOfMill, water-powered grist mill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfMill Context triple: [Dunn’s Falls Park, hasTypeOfMill, water-powered grist mill]
-
A.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
B.
hasMineType
Indicates that an entity is associated with or characterized by a specific type or category of mine.
-
C.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
D.
hasMIC
Indicates that an entity has a specified Minimum Inhibitory Concentration (MIC) value in relation to an antimicrobial agent.
-
E.
hasPetrovType
Indicates that an entity (typically a spacetime or gravitational field) is classified as having a specific Petrov type in the Petrov classification of its Weyl tensor.
- F. None of above. chosen
Provenance (4 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d96179c7648190a05a13991d62bebb |
completed | April 10, 2026, 8:45 p.m. |
Created at: April 9, 2026, 5:18 p.m.