Triple
T24288470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walnut Township, Russell County, Kansas |
E605740
|
entity |
| Predicate | followsCountry |
P155708
|
FINISHED |
| Object | United States federal law |
—
|
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: United States federal law | Statement: [Walnut Township, Russell County, Kansas, followsCountry, United States federal law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsCountry Context triple: [Walnut Township, Russell County, Kansas, followsCountry, United States federal law]
-
A.
followsRegion
Indicates that one region comes directly after another region in a defined order or sequence.
-
B.
followsBy
Indicates that one event, state, or entity occurs or comes immediately after another in a sequence or order.
-
C.
follows
Indicates that one entity comes after, moves behind, or acts in accordance with another entity in time, space, or sequence.
-
D.
followsDisc
Indicates that one entity comes after another in a sequence or order, typically in a discrete or stepwise progression.
-
E.
followsTo
Indicates that one entity moves or proceeds behind another entity toward a specific destination or target.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f57a9a08190b183879ff76071d0 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 18, 2026, 12:08 a.m.