Triple
T3468437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devils Marbles |
E73192
|
entity |
| Predicate | distanceFromTennantCreek_km |
P48979
|
FINISHED |
| Object | approximately 100 |
—
|
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 100 | Statement: [Devils Marbles, distanceFromTennantCreek_km, approximately 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTennantCreek_km Context triple: [Devils Marbles, distanceFromTennantCreek_km, approximately 100]
-
A.
distanceFromTaree
Indicates the measured distance between a given location and the place named Taree.
-
B.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
-
C.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
D.
distanceFromHanaTown (miles)
Indicates the number of miles separating a given place or entity from Hana Town.
-
E.
distanceFromSocorro
Indicates the spatial distance between an entity and the reference location Socorro.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb11ec5881908347bf92883a25ee |
completed | March 8, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69adae05bb0081909dc7e4779d6e05ef |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb1ecb02881908394f197e31431b4 |
completed | March 8, 2026, 5:29 p.m. |
Created at: March 8, 2026, 3:17 p.m.