Triple
T32738703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hijaz scale |
E837160
|
entity |
| Predicate | commonStartingDegree |
P196910
|
FINISHED |
| Object | D |
—
|
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: D | Statement: [Hijaz scale, commonStartingDegree, D]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonStartingDegree Context triple: [Hijaz scale, commonStartingDegree, D]
-
A.
typicalDegreeName
Indicates the standard or commonly used academic degree title associated with an educational program or qualification.
-
B.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
C.
haveDegree
Indicates that an entity possesses or has obtained a specific academic or professional degree.
-
D.
degreeRelatedTo
Indicates a relationship where one entity’s academic degree is connected or relevant to another entity, such as a person, field of study, or institution.
-
E.
hasHighestDegree
Indicates that one entity possesses the highest academic degree attained by another entity.
- 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_69f34936e1748190b797e406e4e9293a |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe6e492bf8819080b25221d13445ea |
completed | May 8, 2026, 11:14 p.m. |
| PD | Predicate disambiguation | batch_69fe6dd33a6881908fe9bbbc184cab51 |
completed | May 8, 2026, 11:12 p.m. |
| PDg | Predicate description generation | batch_69fe6e4801108190a6be6bec2d52a1b9 |
completed | May 8, 2026, 11:14 p.m. |
Created at: May 1, 2026, 1:12 a.m.