Triple
T30956037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hénglóng Guǎngchǎng |
E788677
|
entity |
| Predicate | hasOfficeTenantsType |
P60731
|
FINISHED |
| Object | multinational corporations |
—
|
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: multinational corporations | Statement: [Hénglóng Guǎngchǎng, hasOfficeTenantsType, multinational corporations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficeTenantsType Context triple: [Hénglóng Guǎngchǎng, hasOfficeTenantsType, multinational corporations]
-
A.
hasTenants
Indicates that an entity occupies or rents space from another entity as its tenant.
-
B.
hasOfficeType
Indicates that an entity’s office is classified as a specific type or category of office.
-
C.
hasMajorTenantType
chosen
Indicates that an entity (such as a property or building) is associated with a primary or predominant type of tenant.
-
D.
tenantsSupport
Indicates that one or more tenants provide backing, endorsement, or assistance to another entity or cause.
-
E.
numberOfTenants
Indicates the quantity of tenants associated with a given entity or property.
- 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 29, 2026, 8:54 p.m.