Triple
T26771775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leighlinbridge |
E675096
|
entity |
| Predicate | distanceToCarlowTown_km |
P198057
|
FINISHED |
| Object | approximately 12 |
—
|
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 12 | Statement: [Leighlinbridge, distanceToCarlowTown_km, approximately 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCarlowTown_km Context triple: [Leighlinbridge, distanceToCarlowTown_km, approximately 12]
-
A.
distanceFromCorkCity
Indicates the spatial distance between a given place and Cork City.
-
B.
distanceToTullamore_km
Indicates the physical distance, measured in kilometers, between a given location and Tullamore.
-
C.
distanceFromDublinCityCentre_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the center of Dublin city.
-
D.
distanceToDrogheda_km
Indicates the distance, measured in kilometers, between a given place or object and Drogheda.
-
E.
distanceFromGalway
Indicates the spatial distance separating an entity from the location of Galway.
- 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_69eecda85298819097ee1c38a3d772e7 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fec5c503808190bde0b1829ea43071 |
completed | May 9, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69fec535dd6c8190a6ab85201f5a04a9 |
completed | May 9, 2026, 5:25 a.m. |
| PDg | Predicate description generation | batch_69fec5c3f8248190b835a8e4eba470c4 |
completed | May 9, 2026, 5:27 a.m. |
Created at: April 27, 2026, 4:02 a.m.