Triple
T18773035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Local Hot Cavity |
E459061
|
entity |
| Predicate | hasScientificUncertainties |
P9778
|
FINISHED |
| Object | exact size |
—
|
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: exact size | Statement: [Local Hot Cavity, hasScientificUncertainties, exact size]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScientificUncertainties Context triple: [Local Hot Cavity, hasScientificUncertainties, exact size]
-
A.
hasUncertainty
chosen
Indicates that the relationship or value is associated with some level or type of uncertainty rather than being fully definite or precise.
-
B.
hasScientificValue
Indicates that something possesses significance, usefulness, or merit within scientific research, understanding, or methodology.
-
C.
hasUncertaintyReason
Indicates that there is a specific reason or explanation for why something is uncertain or not known with confidence.
-
D.
hasUncertainNature
Indicates that the nature, status, or characteristics of the relationship or situation are not clearly defined, known, or determined.
-
E.
hasScience
Indicates that an entity possesses, includes, or is associated with a particular scientific discipline, content, or attribute.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e593378a4081909cc1b0856fce7d7d |
completed | April 20, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69e48d1126e4819099607837ed5aadca |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.