Triple
T23902565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakata model of hadrons |
E601092
|
entity |
| Predicate | treatsAsFundamental |
P3979
|
FINISHED |
| Object | proton |
—
|
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: proton | Statement: [Sakata model of hadrons, treatsAsFundamental, proton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsAsFundamental Context triple: [Sakata model of hadrons, treatsAsFundamental, proton]
-
A.
isFundamental
chosen
Indicates that something is a basic, essential, or foundational element upon which other things depend or are built.
-
B.
hasFundamentalDomain
Indicates that a mathematical object (such as a group action or tiling) is associated with a fundamental domain that represents a minimal region whose copies under the given symmetries cover the entire space without overlaps.
-
C.
treatsAsAdvanced
Indicates that one entity regards or handles another entity as if it were advanced in level, status, or complexity.
-
D.
treatsRightAs
Indicates that one entity provides medical or therapeutic treatment to another entity who is identified as the right-hand participant in the relationship.
-
E.
treatsAsSubject
Indicates that one entity regards, handles, or processes another entity in the role or capacity of a subject (e.g., topic, focus, or primary object of consideration).
- 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cddf46948190b8625811725fe41d |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:26 p.m.