Triple
T1103186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zero Degree Calorimeters |
E25426
|
entity |
| Predicate | readout |
P23135
|
FINISHED |
| Object | photomultiplier tubes (in many designs) |
—
|
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 (in many designs) | Statement: [Zero Degree Calorimeters, readout, photomultiplier tubes (in many designs)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readout Context triple: [Zero Degree Calorimeters, readout, photomultiplier tubes (in many designs)]
-
A.
readBy
Indicates that a particular text, document, or content item has been read or consumed by a specific person or agent.
-
B.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
-
C.
rite
Indicates a ceremonial or ritual action performed according to established traditions or religious practices.
-
D.
recall
Indicates that an entity retrieves or brings back into awareness information, events, or items that were previously known, experienced, or stored.
-
E.
readership
Indicates the relationship in which one party reads, follows, or is the audience for the written or published work of another.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c375848190baec4d534f489616 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b7472c848190b0643872f67084a2 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:43 p.m.