Triple
T1276655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fanny’s Ford Trail |
E27228
|
entity |
| Predicate | hasPointOfInterest |
P3449
|
FINISHED |
| Object | historic ford sites on the Eno River |
—
|
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: historic ford sites on the Eno River | Statement: [Fanny’s Ford Trail, hasPointOfInterest, historic ford sites on the Eno River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPointOfInterest Context triple: [Fanny’s Ford Trail, hasPointOfInterest, historic ford sites on the Eno River]
-
A.
hasAttractionNearby
chosen
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
B.
placesWithin
Indicates that one place or area is located entirely inside the boundaries of another place or area.
-
C.
featureOfInterest
Indicates the entity or object that is the primary subject or focus of the described observation, measurement, or analysis.
-
D.
touristAttractionIn
Indicates that a place functions as a tourist attraction located within a specified geographic area or entity.
-
E.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
- 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4bee0be808190a8ccac6a41851fdd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.