Triple
T10265491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Meredith |
E240700
|
entity |
| Predicate | degreeReceived |
P6
|
FINISHED |
| Object | political science |
—
|
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: political science | Statement: [James Meredith, degreeReceived, political science]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degreeReceived Context triple: [James Meredith, degreeReceived, political science]
-
A.
degreeGrantedBy
Indicates that a specific academic degree was officially conferred by a particular granting institution.
-
B.
academicDegree
chosen
Indicates that an entity holds or has been awarded a specific academic degree.
-
C.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
-
D.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
E.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2872830819080fdfa816167d04c |
completed | April 7, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ef6e6c81908a8ee52e4d28127b |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:33 a.m.