Triple
T34025459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas, Queensland |
E872495
|
entity |
| Predicate | distanceToGoondiwindi_km |
P205284
|
FINISHED |
| Object | approximately 115 |
—
|
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 115 | Statement: [Texas, Queensland, distanceToGoondiwindi_km, approximately 115]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGoondiwindi_km Context triple: [Texas, Queensland, distanceToGoondiwindi_km, approximately 115]
-
A.
distanceTo_Quirindi_km
Indicates the distance, measured in kilometers, from a given entity or location to Quirindi.
-
B.
directionFromGoondiwindi
Indicates the compass direction in which one location lies when measured starting from Goondiwindi.
-
C.
distanceFromDarwin
Indicates the spatial distance between an entity and the location Darwin.
-
D.
distanceToGympie
Indicates the spatial distance between a given location and the town or area of Gympie.
-
E.
distanceToKununurra_km
Indicates the distance, measured in kilometers, from a given location to Kununurra.
- 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_69f349a19ad88190ab586f010c804a8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:51 a.m.