Triple
T6033880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BaBar detector |
E134369
|
entity |
| Predicate | vertexDetectorTechnology |
P68875
|
FINISHED |
| Object | silicon microstrip |
—
|
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: silicon microstrip | Statement: [BaBar detector, vertexDetectorTechnology, silicon microstrip]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vertexDetectorTechnology Context triple: [BaBar detector, vertexDetectorTechnology, silicon microstrip]
-
A.
detectorType
Indicates the specific kind or category of detector associated with an entity or measurement.
-
B.
numberOfDetectors
Indicates the quantity of detectors associated with or involved in a given entity or system.
-
C.
numberOfMainDetectors
Indicates the quantity of primary detectors associated with or used in a given context or system.
-
D.
viewOnTechnology
Indicates how an entity perceives, evaluates, or holds opinions about technology and its role or impact.
-
E.
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.
- 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.