Triple
T16748533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CiteScore |
E407015
|
entity |
| Predicate | fieldNormalization |
P124489
|
FINISHED |
| Object | no explicit field normalization in base metric |
—
|
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: no explicit field normalization in base metric | Statement: [CiteScore, fieldNormalization, no explicit field normalization in base metric]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldNormalization Context triple: [CiteScore, fieldNormalization, no explicit field normalization in base metric]
-
A.
normalizationInvolves
Indicates that a normalization process includes or makes use of a particular component, step, or element as part of its execution.
-
B.
normalizationAttempt
Indicates an effort to convert something into a standard or consistent form according to defined rules or criteria.
-
C.
oftenNormalizedTo
Indicates that one entity is frequently converted, mapped, or standardized into the form or representation of another entity.
-
D.
refinesNormalization
Indicates that one normalization process or scheme improves, clarifies, or makes more precise another existing normalization.
-
E.
usesNormalization
Indicates that one entity applies or relies on a normalization process or technique in relation to another entity or data.
- F. None of above. chosen
Provenance (4 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa2532ac81908e5ee5148e35f92e |
completed | April 18, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69e319cbd79c8190a03587a61c18bec0 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:21 a.m.