Triple
T4596482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puckman |
E100215
|
entity |
| Predicate | representsInstitutionFocus |
P43754
|
FINISHED |
| Object | engineering |
—
|
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: engineering | Statement: [Puckman, representsInstitutionFocus, engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsInstitutionFocus Context triple: [Puckman, representsInstitutionFocus, engineering]
-
A.
focusesOnInstitutionControl
Indicates that the primary emphasis or concern is on controlling or governing institutions and their decision-making processes.
-
B.
involvesInstitution
Indicates that an action, event, or relationship includes or is associated with an institution as a participating party.
-
C.
centralInstitutionOf
Indicates that one institution serves as the primary or main institutional center for another entity, such as an organization, system, or region.
-
D.
inInstitution
Indicates that an entity is located within, belongs to, or is formally associated with a particular institution.
-
E.
regionOfAcademicFocus
chosen
Indicates the academic subject area or discipline that an entity (such as a person or program) primarily concentrates on or specializes in.
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd594055dc8190a50f1b4be2be1ba0 |
completed | March 20, 2026, 2:27 p.m. |
| PD | Predicate disambiguation | batch_69bd522c811c81909aae4feadae33174 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:11 p.m.