Triple
T1166225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Electromagnetic Calorimeter |
E24804
|
entity |
| Predicate | readoutTechnology |
P6774
|
FINISHED |
| Object | photomultiplier tubes |
—
|
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: photomultiplier tubes | Statement: [Electromagnetic Calorimeter, readoutTechnology, photomultiplier tubes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readoutTechnology Context triple: [Electromagnetic Calorimeter, readoutTechnology, photomultiplier tubes]
-
A.
readout
Indicates that one entity reports, displays, or outputs the measured or computed value of another entity.
-
B.
technologicalFeature
chosen
Indicates that one entity possesses, exhibits, or is characterized by a specific technological capability, component, or functionality in relation to another entity.
-
C.
displays
Indicates that one entity visually presents or shows another entity’s content or information.
-
D.
readBy
Indicates that a particular text, document, or content item has been read or consumed by a specific person or agent.
-
E.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bccc62a88190882d8801908015a4 |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb548c1481909092626c572d8782 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.