Triple
T11970458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhea County |
E284904
|
entity |
| Predicate | hasHistoricEventYear |
P102571
|
FINISHED |
| Object | 1925 |
—
|
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: 1925 | Statement: [Rhea County, hasHistoricEventYear, 1925]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricEventYear Context triple: [Rhea County, hasHistoricEventYear, 1925]
-
A.
hasHistoricalEvent
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
B.
hasHistoricalOriginInYear
Indicates that something first originated, began, or came into existence in a specified calendar year.
-
C.
yearOfEventSupport
Indicates the specific year in which support for a particular event occurred or was provided.
-
D.
hasYearOfNamesakeEvent
Indicates the specific year in which the event that a namesake is based on or named after took place.
-
E.
hasHistoricSignificanceFor
Indicates that something holds notable historical importance or relevance for a particular entity or group.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037bee54819085242a3ef3e286f9 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:46 p.m.