Triple
T35560989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swift BAT |
E1027634
|
entity |
| Predicate | hasDetectorArea |
P199687
|
FINISHED |
| Object | about 5200 square centimeters |
—
|
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: about 5200 square centimeters | Statement: [Swift BAT, hasDetectorArea, about 5200 square centimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDetectorArea Context triple: [Swift BAT, hasDetectorArea, about 5200 square centimeters]
-
A.
hasObservationArea
Indicates that an entity possesses or includes a designated area from which observations or monitoring activities are conducted.
-
B.
hasFarDetector
Indicates that an entity is equipped with or associated with a detector positioned at a relatively large distance from a reference point or source.
-
C.
isDetector
Indicates that one entity functions as a detector for, or is responsible for detecting, another entity or phenomenon.
-
D.
hasDisplayArea
Indicates that an entity includes or is associated with a specific physical or virtual area used for displaying content or items.
-
E.
hasFarDetectorFunction
Indicates that an entity possesses a function or capability specifically related to detecting objects, signals, or phenomena at a long or extended distance.
- 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff4fc6077c8190b8fd9b43fcfde986 |
completed | May 9, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69ff4e61fb648190a72f7918961ece9c |
completed | May 9, 2026, 3:10 p.m. |
| PDg | Predicate description generation | batch_69ff4fc5289c819084abd5ede185e96b |
completed | May 9, 2026, 3:16 p.m. |
Created at: May 3, 2026, 4:04 p.m.