Triple
T6111161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peierls transition |
E136241
|
entity |
| Predicate | effectOnFermiSurface |
P40373
|
FINISHED |
| Object | partial or complete gapping of the Fermi surface |
—
|
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: partial or complete gapping of the Fermi surface | Statement: [Peierls transition, effectOnFermiSurface, partial or complete gapping of the Fermi surface]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnFermiSurface Context triple: [Peierls transition, effectOnFermiSurface, partial or complete gapping of the Fermi surface]
-
A.
effectOnRepresentation
Indicates how one entity influences, alters, or determines the form, quality, or characteristics of another entity’s representation.
-
B.
effectOnSystem
chosen
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
C.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
D.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
E.
effectiveArea
Indicates the portion of a surface or region that actually contributes to a specified effect, such as performance, interaction, or impact, within a given context.
- 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_69c0089ea6f88190b349be53e04b4f5f |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bbbbea88190b889a7c30af1d71a |
completed | March 22, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c049f80e2081909b7d84a104cda68d |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.