Triple
T3616210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DUNE experiment |
E76605
|
entity |
| Predicate | farDetectorCity |
P50451
|
FINISHED |
| Object | Lead |
—
|
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: Lead | Statement: [DUNE experiment, farDetectorCity, Lead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: farDetectorCity Context triple: [DUNE experiment, farDetectorCity, Lead]
-
A.
cityWide
Indicates that something applies to, affects, or extends across an entire city.
-
B.
coversCity
Indicates that one entity extends over, includes, or geographically encompasses the area of a specified city.
-
C.
cityPanorama
Indicates a wide, comprehensive visual view or representation of a cityscape, typically encompassing many of its features in a single scene.
-
D.
nearbyFrontier
Indicates that one entity is located close to a boundary or frontier region associated with another entity.
-
E.
passesNearCity
Indicates that the path, route, or trajectory of one entity goes close to, but not necessarily through, a specified city.
- 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_69ad85dae2fc81908d1ceadbc6af0089 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc27c98088190a493c9eddf6b206a |
completed | March 8, 2026, 6:39 p.m. |
| PD | Predicate disambiguation | batch_69adb83f1e4c8190ab501c1c05b14c08 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb9bbb62c8190989629ca11733e1b |
completed | March 8, 2026, 6:02 p.m. |
Created at: March 8, 2026, 3:23 p.m.