Triple
T20308806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lakeside Office Park |
E510178
|
entity |
| Predicate | isInBusinessDistrictOf |
P16988
|
FINISHED |
| Object | Wakefield, Massachusetts |
—
|
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: Wakefield, Massachusetts | Statement: [Lakeside Office Park, isInBusinessDistrictOf, Wakefield, Massachusetts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInBusinessDistrictOf Context triple: [Lakeside Office Park, isInBusinessDistrictOf, Wakefield, Massachusetts]
-
A.
isInBusinessDistrict
chosen
Indicates that an entity is located within a designated business or commercial district area.
-
B.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
C.
isPartOfBusinessArea
Indicates that one entity belongs to, is included within, or falls under the scope of a particular business area.
-
D.
isShoppingDistrict
Indicates that a location functions primarily as a shopping district, characterized by a concentration of retail stores and commercial shopping activity.
-
E.
isBusinessCenter
Indicates that a location or facility functions primarily as a hub for business activities, services, or operations.
- 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_69e0b4c7491c8190961113c4283b10b0 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6774286a88190800d6b062f3d7a9f |
completed | April 20, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:18 a.m.