Triple
T1096186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SLD |
E24276
|
entity |
| Predicate | measuredProperty |
P23071
|
FINISHED |
| Object | Z boson properties |
—
|
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: Z boson properties | Statement: [SLD, measuredProperty, Z boson properties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: measuredProperty Context triple: [SLD, measuredProperty, Z boson properties]
-
A.
hasMeasurement
Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
-
B.
measuredFrom
Indicates that a measurement or value is determined relative to, or using, a specified reference point or source.
-
C.
wasPreviouslyMeasuredAs
Indicates that an entity had a specific measurement or value at an earlier time, which may differ from its current measurement.
-
D.
measuredAt
Indicates the time or point at which a measurement was taken or recorded for an entity or event.
-
E.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99ffb3481908cd168b6c58e1c6d |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b7448c148190a3c9a4158ebd05b4 |
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, 7:42 p.m.