Triple
T30933613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Vance |
E788059
|
entity |
| Predicate | neighborBusinessOf |
P71206
|
FINISHED |
| Object | Dunder Mifflin Scranton |
—
|
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: Dunder Mifflin Scranton | Statement: [Bob Vance, neighborBusinessOf, Dunder Mifflin Scranton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neighborBusinessOf Context triple: [Bob Vance, neighborBusinessOf, Dunder Mifflin Scranton]
-
A.
nearbyEconomicActivity
chosen
Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
-
B.
namedAfterNearbyPlace
Indicates that an entity’s name is derived from or inspired by a geographically nearby place.
-
C.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
-
D.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
E.
hasMajorCompanyNearby
Indicates that a location or entity is situated close to at least one large or significant company.
- 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_69f224c0b7fc819090cb89df60d23653 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 29, 2026, 8:52 p.m.