Triple
T33588394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | electron antineutrino |
E860351
|
entity |
| Predicate | hasInteractionCrossSection |
P38062
|
FINISHED |
| Object | extremely small |
—
|
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: extremely small | Statement: [electron antineutrino, hasInteractionCrossSection, extremely small]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInteractionCrossSection Context triple: [electron antineutrino, hasInteractionCrossSection, extremely small]
-
A.
interactionCrossSection
chosen
Indicates the effective likelihood or probability that a specified interaction or reaction will occur between entities (such as particles) under given conditions.
-
B.
hasCrossSection
Indicates that one entity represents or possesses the cross-sectional shape, profile, or slice of another entity.
-
C.
hasCross
Indicates that one entity possesses, displays, or is marked by a cross in relation to another entity or context.
-
D.
hasInteractionEffects
Indicates that one entity’s presence, action, or state alters, influences, or modifies the behavior, effect, or outcome associated with another entity.
-
E.
hasInteraction
Indicates that there is some form of interaction or mutual action occurring 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fff4530f908190afe9387f732c2b7e |
completed | May 10, 2026, 2:58 a.m. |
| PD | Predicate disambiguation | batch_69fff3c01a64819091196875b0c88607 |
completed | May 10, 2026, 2:56 a.m. |
Created at: May 1, 2026, 1:40 a.m.