Triple
T5830712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuck School of Business |
E129336
|
entity |
| Predicate | hasCareerService |
P67427
|
FINISHED |
| Object | career development office |
—
|
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: career development office | Statement: [Tuck School of Business, hasCareerService, career development office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCareerService Context triple: [Tuck School of Business, hasCareerService, career development office]
-
A.
hasCareerTrack
Indicates that an entity is associated with or follows a particular career path or professional progression.
-
B.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
-
C.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
D.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
E.
supportedCareerOf
Indicates that one entity provided assistance, resources, or endorsement that helped establish or advance another entity’s career.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69c044a9c4f0819081b8c196932883f6 |
completed | March 22, 2026, 7:36 p.m. |
Created at: March 22, 2026, 3:54 p.m.