Triple
T3779251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cecil Calvert, 2nd Baron Baltimore |
E83379
|
entity |
| Predicate | matriculationYear |
P50887
|
FINISHED |
| Object | 1621 |
—
|
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: 1621 | Statement: [Cecil Calvert, 2nd Baron Baltimore, matriculationYear, 1621]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matriculationYear Context triple: [Cecil Calvert, 2nd Baron Baltimore, matriculationYear, 1621]
-
A.
lastSittingYear
Indicates the specific year in which an entity most recently held a sitting, session, or term.
-
B.
majorStudyYear
Indicates the academic year in which an entity (typically a student) is primarily engaged in a particular course of study or major.
-
C.
fullCollegeStatusYear
Indicates the year in which an entity attained or was recognized with full college status.
-
D.
ordinationYear
Indicates the year in which an individual was formally ordained to a religious office or role.
-
E.
isStudiedIn
Indicates that a subject (such as a topic, field, or phenomenon) is examined, researched, or learned about within a particular context, environment, or discipline.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc7948848190adc96b0513bd5c97 |
completed | March 8, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69adc050cc5c81909d9855f866f3c26d |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc0fe3e3c8190bd886c7745c172a0 |
completed | March 8, 2026, 6:33 p.m. |
Created at: March 8, 2026, 3:36 p.m.