Triple
T3573985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FEROS spectrograph |
E75641
|
entity |
| Predicate | hasCalibration |
P50659
|
FINISHED |
| Object | ThAr comparison lamp |
—
|
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: ThAr comparison lamp | Statement: [FEROS spectrograph, hasCalibration, ThAr comparison lamp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCalibration Context triple: [FEROS spectrograph, hasCalibration, ThAr comparison lamp]
-
A.
supportsHardwareCalibration
Indicates that one entity provides the capability or functionality to perform calibration operations on another entity’s hardware.
-
B.
calibratedFor
Indicates that something has been adjusted or tuned to operate accurately or optimally for a specific target, condition, or context.
-
C.
hasMeasurement
Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
-
D.
hasSensor
Indicates that one entity is equipped with, contains, or uses a particular sensor.
-
E.
hasMeter
Indicates that one entity possesses, uses, or is associated with a specific meter (a measuring device or metrical pattern).
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0d928f08190830347b3b032178a |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb8364d848190a96a9bc7a6126af2 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adba25c66c81909a05a97327828c41 |
completed | March 8, 2026, 6:04 p.m. |
Created at: March 8, 2026, 3:21 p.m.