Triple
T1297801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulliken electronegativity scale |
E27692
|
entity |
| Predicate | IstandsFor |
P590
|
FINISHED |
| Object | ionization energy |
—
|
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: ionization energy | Statement: [Mulliken electronegativity scale, IstandsFor, ionization energy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: IstandsFor Context triple: [Mulliken electronegativity scale, IstandsFor, ionization energy]
-
A.
standsFor
chosen
Indicates that one entity represents, symbolizes, or serves as a substitute or abbreviation for another entity.
-
B.
callSignMeaning
Indicates that an entity’s call sign conveys or is associated with a particular meaning or interpretation.
-
C.
symbolizes
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
-
D.
meaningOfPhrase
Indicates that one entity expresses or defines the semantic content or interpretation of a given phrase.
-
E.
inscriptionMeaning
Indicates that an inscription conveys a particular meaning, message, or content.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bee64d908190b6a9bb479959d523 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.