Triple
T7233150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Tippecanoe |
E154950
|
entity |
| Predicate | hasAssociatedYear |
P75923
|
FINISHED |
| Object | 1811 |
—
|
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: 1811 | Statement: [Old Tippecanoe, hasAssociatedYear, 1811]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedYear Context triple: [Old Tippecanoe, hasAssociatedYear, 1811]
-
A.
hasYearType
Indicates a relationship where an entity is associated with a specific classification or category of year (such as calendar, fiscal, academic, or other year type).
-
B.
hasTypeOfYear
Indicates that a given year is classified as belonging to a specific type or category of year (e.g., fiscal, academic, leap).
-
C.
accessionYear
Indicates the calendar year in which an item, record, or entity was formally added to or registered within a collection, system, or institution.
-
D.
hasNumberInYear
Indicates that a specific number is associated with or occurs within a given year.
-
E.
authorizationYear
Indicates the year in which an official approval, permission, or authorization for something was granted.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea552a688190a00f5d0ad982f787 |
completed | March 27, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69c6e7644648819096a5e2de5d0dbe97 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6ea539f5c81908001524149903559 |
completed | March 27, 2026, 8:36 p.m. |
Created at: March 27, 2026, 2:55 p.m.