Triple
T16492980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu experiment |
E400610
|
entity |
| Predicate | interactionTypeStudied |
P96076
|
FINISHED |
| Object | weak interaction |
—
|
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: weak interaction | Statement: [Wu experiment, interactionTypeStudied, weak interaction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interactionTypeStudied Context triple: [Wu experiment, interactionTypeStudied, weak interaction]
-
A.
usedInteractionType
chosen
Indicates the specific type or category of interaction that was used between the related entities.
-
B.
typicalInteraction
Indicates the usual or most common way in which two entities interact or relate to each other.
-
C.
interventionType
Indicates the specific kind or category of action, treatment, or measure applied in an intervention.
-
D.
studyType
Indicates the kind or category of study or research methodology associated with an entity or activity.
-
E.
engagementType
Indicates the specific kind or category of engagement or interaction that occurs between the related entities.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e30cb648190a52cb32896c4ac5a |
completed | April 18, 2026, 7:09 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:13 a.m.