Triple
T21163541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon, Ireland |
E521499
|
entity |
| Predicate | distanceToEnnis |
P143122
|
FINISHED |
| Object | approximately 22 km |
—
|
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: approximately 22 km | Statement: [Shannon, Ireland, distanceToEnnis, approximately 22 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToEnnis Context triple: [Shannon, Ireland, distanceToEnnis, approximately 22 km]
-
A.
distanceToAmarillo
Indicates the spatial distance between a given entity and the location Amarillo.
-
B.
distanceToDickinson
Indicates the spatial distance between a given entity and Dickinson.
-
C.
approxDistanceFromEnsenada
Indicates that one entity is located at an approximate distance from the reference location Ensenada.
-
D.
distanceToFortWorth
Indicates the spatial distance between a given location and the city of Fort Worth.
-
E.
approximateDistanceToElPaso
Indicates that one entity has an estimated or rough distance measurement relative to the location of El Paso.
- 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_69e0b50d1ea481909c07e63c3ead9316 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72533fe88819082e14d71c36140be |
completed | April 21, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69e5f5f8a5bc819081918c7fa8e4496d |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f993240c8190847c0b08e65726c8 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 2:59 p.m.