Triple
T37045488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlos E. Muñoz |
E916894
|
entity |
| Predicate | hasAcademicSupervisor |
P192530
|
FINISHED |
| Object | Carlos Kenig |
—
|
NE NERFINISHED |
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: Carlos Kenig | Statement: [Carlos E. Muñoz, hasAcademicSupervisor, Carlos Kenig]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcademicSupervisor Context triple: [Carlos E. Muñoz, hasAcademicSupervisor, Carlos Kenig]
-
A.
hasDoctoralStudentsThrough
Indicates that one entity has doctoral students indirectly through another entity, such as via co-supervision, program affiliation, or intermediary supervision relationships.
-
B.
academicAdvisorOfAuthor
Indicates that one person serves as the academic advisor or mentor responsible for guiding the author in their scholarly or research activities.
-
C.
hasDoctoralStudents
Indicates that a person serves as the doctoral advisor or supervisor of one or more doctoral students.
-
D.
hasAcademicStaff
Indicates that an institution or organization employs or is associated with one or more academic staff members.
-
E.
hasAcademicComponent
Indicates that something includes, involves, or is associated with an academic or educational element as part of its structure or content.
- 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_69f76e93ec4c8190be81cf87354d9155 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69fd0d0aebac8190868a7714ddb4f1fd |
completed | May 7, 2026, 10:07 p.m. |
Created at: May 3, 2026, 4:14 p.m.