Triple
T6058187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silicon Strip Detector |
E134965
|
entity |
| Predicate | stripOrientation |
P4984
|
FINISHED |
| Object | can be orthogonal in double-sided detectors |
—
|
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: can be orthogonal in double-sided detectors | Statement: [Silicon Strip Detector, stripOrientation, can be orthogonal in double-sided detectors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stripOrientation Context triple: [Silicon Strip Detector, stripOrientation, can be orthogonal in double-sided detectors]
-
A.
exportOrientation
Indicates that an entity’s activities, production, or strategy are primarily directed toward serving foreign or international markets rather than domestic ones.
-
B.
hasStripeOrientation
chosen
Indicates the directional arrangement or alignment of stripes present on an entity.
-
C.
hasOrientation
Indicates that one entity is positioned or directed in a specific spatial or conceptual alignment relative to a reference frame or another entity.
-
D.
valueOrientation
Indicates how an entity’s preferences, priorities, or attitudes are directed toward particular values or value systems.
-
E.
sessionOrientation
Indicates the directional or spatial alignment relationship established between entities within a session or interaction context.
- F. None of above.
Provenance (3 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0570d00e88190b2d8d596e40378d9 |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049edc6f0819092ca620d9073ad26 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:10 p.m.