Triple
T11713762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop Tuff |
E278438
|
entity |
| Predicate | weldingDegree |
P95385
|
FINISHED |
| Object | strongly welded in central parts |
—
|
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: strongly welded in central parts | Statement: [Bishop Tuff, weldingDegree, strongly welded in central parts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weldingDegree Context triple: [Bishop Tuff, weldingDegree, strongly welded in central parts]
-
A.
degreeNumber
Indicates the specific numeric value assigned to a degree, such as its level, rank, or sequence number.
-
B.
notionOfDegree
chosen
Indicates a relationship where one entity specifies or characterizes the degree, intensity, or extent to which a property or condition applies to another entity.
-
C.
certificationLevel
Indicates the specific rank or degree of formal qualification or authorization that an entity has achieved within a defined certification system.
-
D.
degreeOver
Indicates that one entity’s degree, level, or extent exceeds that of another entity.
-
E.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4bf54d88190a8e07fbbf8d9e962 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.