Triple
T917983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lerner Enterprises |
E19812
|
entity |
| Predicate | hasAreaOfBusiness |
P16009
|
FINISHED |
| Object | commercial real estate |
—
|
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: commercial real estate | Statement: [Lerner Enterprises, hasAreaOfBusiness, commercial real estate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaOfBusiness Context triple: [Lerner Enterprises, hasAreaOfBusiness, commercial real estate]
-
A.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
B.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
C.
hasBusinessDivision
Indicates that an organization includes or is composed of a specific business division as a subordinate unit.
-
D.
hasMajorBusinessLine
chosen
Indicates that an entity conducts a primary or significant line of business in a specified area, sector, or activity.
-
E.
hasServiceAreas
Indicates that an entity provides services within, or is operational across, specific geographic or functional areas.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b388f0bc8190a087222636135ba5 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b2944ff88190a260be5355132ba5 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.