Triple
T6033881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BaBar detector |
E134369
|
entity |
| Predicate | trackingDetectorTechnology |
P68876
|
FINISHED |
| Object | gas-filled drift chamber |
—
|
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: gas-filled drift chamber | Statement: [BaBar detector, trackingDetectorTechnology, gas-filled drift chamber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackingDetectorTechnology Context triple: [BaBar detector, trackingDetectorTechnology, gas-filled drift chamber]
-
A.
trackingTechnology
Indicates that one entity uses or is associated with a technology designed to monitor, record, or follow the behavior, location, or interactions of another entity.
-
B.
trackingType
Indicates the method or category by which an entity’s movement, status, or progress is monitored or recorded.
-
C.
trackingAvailable
Indicates that tracking information or functionality is available for the associated item, process, or interaction.
-
D.
technologyTrackExample
Indicates a relationship where one entity serves as an example or instance of a particular technology track associated with another entity.
-
E.
detectorType
Indicates the specific kind or category of detector associated with an entity or measurement.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b220608190b156be95632cf3b3 |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049e9a68c81909da0cfe4779ce9b5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:08 p.m.