Triple
T25967272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bells Corners |
E645703
|
entity |
| Predicate | hasNearbyEmploymentType |
P176689
|
FINISHED |
| Object | technology sector |
—
|
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: technology sector | Statement: [Bells Corners, hasNearbyEmploymentType, technology sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyEmploymentType Context triple: [Bells Corners, hasNearbyEmploymentType, technology sector]
-
A.
hasNearbyIndustry
Indicates that an entity is located close to one or more industrial facilities or activities.
-
B.
hasOccupationInWork
Indicates that an entity holds or performs a specific occupation within a particular work, project, or creative production.
-
C.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
D.
worksNear
Indicates that one entity performs its work or duties in close physical proximity to another entity.
-
E.
commonEmployment
Indicates that two or more entities share the same employer or have worked for the same 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_69e77e85efc08190997da7fcf98bd300 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69f6e60109648190947a64ca4ce81a3a |
completed | May 3, 2026, 6:06 a.m. |
Created at: April 22, 2026, 8:48 a.m.