Triple
T37565576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haileybury School of Mines |
E933945
|
entity |
| Predicate | hasPracticalTrainingComponent |
P155286
|
FINISHED |
| Object | fieldwork |
—
|
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: fieldwork | Statement: [Haileybury School of Mines, hasPracticalTrainingComponent, fieldwork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPracticalTrainingComponent Context triple: [Haileybury School of Mines, hasPracticalTrainingComponent, fieldwork]
-
A.
hasPracticum
chosen
Indicates that an entity includes, requires, or is associated with a practical training or hands-on learning component.
-
B.
hasFieldTrainingComponent
Indicates that an entity includes or is associated with a component involving practical, in-the-field training activities.
-
C.
hasHandsOnTraining
Indicates that an entity has received practical, experiential instruction or practice in performing a specific task or activity.
-
D.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
E.
hasPreclinicalTraining
Indicates that an entity has completed or possesses training that occurs before clinical practice or clinical application.
- 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_69f76ecb4acc8190b53f96d0b013e415 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.