Triple
T110299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Bessemer |
E2233
|
entity |
| Predicate | educatedIn |
P7336
|
FINISHED |
| Object | self-taught engineering and metallurgy |
—
|
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: self-taught engineering and metallurgy | Statement: [Henry Bessemer, educatedIn, self-taught engineering and metallurgy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educatedIn Context triple: [Henry Bessemer, educatedIn, self-taught engineering and metallurgy]
-
A.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
B.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
C.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
educationSystem
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
-
E.
viewOnEducation
Indicates a stance, opinion, or perspective that an entity holds regarding education or educational matters.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258b58efc8190959c86f73d67b744 |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25641058c8190b5b64509b35d8176 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a258b30f6c8190be2181f30c40e04d |
completed | Feb. 28, 2026, 2:53 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.