Triple
T32476315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobu Group |
E829984
|
entity |
| Predicate | realEstateBusinessType |
P5777
|
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: [Tobu Group, realEstateBusinessType, commercial real estate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realEstateBusinessType Context triple: [Tobu Group, realEstateBusinessType, commercial real estate]
-
A.
realEstateCategory
chosen
Indicates the classification of a property into a specific type or category within real estate (e.g., residential, commercial, industrial).
-
B.
realEstate
Indicates a relationship where an entity owns, manages, or is otherwise associated with real property such as land or buildings.
-
C.
realEstateProject
Indicates a relationship where an entity is involved in, associated with, or represents a specific real estate development project.
-
D.
typeOfEnterpriseBuilt
Indicates the specific kind or category of enterprise that has been constructed or established.
-
E.
businessLocationType
Indicates the type or category of location where a business operates or is situated.
- 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_69f3491ff3b48190b50a7fa00bb05b1f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c3913f108190b2e10106534b6392 |
completed | May 3, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69f6ba700a708190ab6db62791e43774 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:58 a.m.