Triple
T1390245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arm2 detector |
E29937
|
entity |
| Predicate | hasCoordinateCoverage |
P22467
|
FINISHED |
| Object | pseudorapidity η > 8 |
—
|
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: pseudorapidity η > 8 | Statement: [Arm2 detector, hasCoordinateCoverage, pseudorapidity η > 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoordinateCoverage Context triple: [Arm2 detector, hasCoordinateCoverage, pseudorapidity η > 8]
-
A.
hasCoordinates
Indicates that an entity is associated with specific spatial coordinates that define its position in a given reference system.
-
B.
hasCoordinatesType
chosen
Indicates that an entity is associated with a specific type or system of coordinates used to define its position.
-
C.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
-
D.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
-
E.
hasLandCoverage
Indicates that a specified area or region is covered or occupied by a particular type of land surface or land use.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c35e023c8190b45688796d90534b |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4beffcf808190ab4cd0271257ce63 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.