Triple
T23348093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Singh |
E591922
|
entity |
| Predicate | foundedOrganizationSpecialization |
P151971
|
FINISHED |
| Object | travel and expense management |
—
|
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: travel and expense management | Statement: [Steve Singh, foundedOrganizationSpecialization, travel and expense management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foundedOrganizationSpecialization Context triple: [Steve Singh, foundedOrganizationSpecialization, travel and expense management]
-
A.
foundedOrganization
Indicates that an entity established or created an organization.
-
B.
associatedCompanySpecialization
Indicates that a company is linked to a particular area of specialization or expertise.
-
C.
foundedOrganizationType
Indicates that an entity established or created an organization of a specified type (e.g., company, nonprofit, institution).
-
D.
institutionSpecialization
Indicates that an institution focuses on, is dedicated to, or has expertise in a particular field, domain, or area of activity.
-
E.
parentOrganizationSpecialty
Indicates that a specialty or sub-discipline is associated with, or falls under the scope of, a broader parent organization.
- 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1983840a481908c503e47ef2158e3 |
completed | April 29, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69effcfd8d288190937a887fe6023c11 |
completed | April 28, 2026, 12:19 a.m. |
| PDg | Predicate description generation | batch_69f01d88b4ec8190a2a17a88e0eda178 |
completed | April 28, 2026, 2:38 a.m. |
Created at: April 17, 2026, 5:19 p.m.