Triple
T16857578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yukawa coupling |
E409824
|
entity |
| Predicate | largestExample |
P58835
|
FINISHED |
| Object | top quark Yukawa coupling |
—
|
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: top quark Yukawa coupling | Statement: [Yukawa coupling, largestExample, top quark Yukawa coupling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestExample Context triple: [Yukawa coupling, largestExample, top quark Yukawa coupling]
-
A.
majorExample
chosen
Indicates that one entity serves as a primary or most significant example or instance of another entity.
-
B.
largestSpan
Indicates that the referenced entity has the greatest extent or coverage (in distance, time, or range) among a set of comparable spans.
-
C.
largestPartIn
Indicates that one entity is the largest component or segment contained within another entity.
-
D.
isLargestOf
Indicates that one entity has the greatest size, extent, or magnitude among a specified set of entities.
-
E.
containsSomeOfLargestKnown
Indicates that an entity includes within it one or more items that rank among the largest known of their kind.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37e34b88190bb4468424e2edf2d |
completed | April 18, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.