Triple
T5877561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwinger model |
E130663
|
entity |
| Predicate | hasFieldContent |
P22683
|
FINISHED |
| Object | Dirac fermion |
—
|
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: Dirac fermion | Statement: [Schwinger model, hasFieldContent, Dirac fermion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFieldContent Context triple: [Schwinger model, hasFieldContent, Dirac fermion]
-
A.
hasContentFrom
chosen
Indicates that one entity’s content is derived from, includes, or is based on another entity.
-
B.
hasFieldName
Indicates that one entity is associated with, or identified by, a specific field name in a data structure or schema.
-
C.
hasFiberContent
Indicates that one entity contains a specified amount or level of dietary fiber.
-
D.
hasFieldContribution
Indicates that an entity has made a contribution or provided input within a particular field, domain, or area of activity.
-
E.
hasFieldLength
Indicates that an entity possesses a field whose length (such as number of characters or size) is specified or constrained.
- 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_69c0085523688190bfd487479ce819e6 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0432fea5881909f5c291dd8db6105 |
completed | March 22, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69c033499ca08190bd26cee5b03f6306 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:57 p.m.