Triple
T25848898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmington and Western Railroad |
E651145
|
entity |
| Predicate | holidayEvents |
P5814
|
FINISHED |
| Object | special holiday trains |
—
|
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: special holiday trains | Statement: [Wilmington and Western Railroad, holidayEvents, special holiday trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holidayEvents Context triple: [Wilmington and Western Railroad, holidayEvents, special holiday trains]
-
A.
holidayType
Indicates the specific category or kind of holiday associated with an event or date (e.g., public, religious, national, or personal).
-
B.
holidayRole
Indicates the specific function, duty, or part an entity plays in relation to a holiday or holiday-related event.
-
C.
ethnicHoliday
Indicates a holiday that is specifically associated with, celebrated by, or originating from a particular ethnic group.
-
D.
holidayAssociation
chosen
Indicates a relationship where one entity is connected to, themed around, or designated for a particular holiday.
-
E.
relatedHoliday
Indicates that there is an association or connection between two holidays, such as thematic, temporal, cultural, or contextual relatedness.
- 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_69e7ab39035c8190be15c8aaee1bb858 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f60239fb6881908503759ddd6b3fb1 |
completed | May 2, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 7:57 a.m.