Triple
T23068839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaki business district |
E575132
|
entity |
| Predicate | hasOfficeFunction |
P5164
|
FINISHED |
| Object | regional headquarters |
—
|
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: regional headquarters | Statement: [Osaki business district, hasOfficeFunction, regional headquarters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficeFunction Context triple: [Osaki business district, hasOfficeFunction, regional headquarters]
-
A.
hasOffice
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
-
B.
hasOfficeType
chosen
Indicates that an entity’s office is classified as a specific type or category of office.
-
C.
hasBackOfficeFunctionsIn
Indicates that an entity’s back-office operations or support functions are performed or located in a specified place or organizational unit.
-
D.
hasAssociatedOffice
Indicates that an entity is linked to or connected with a particular office in an official or functional capacity.
-
E.
hasProperOffice
Indicates that an entity maintains an officially designated, appropriate office or place of business.
- 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_69e245bd6e4c8190bb8942245b68cad5 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f189a5aa4081909b3f0dc92877323d |
completed | April 29, 2026, 4:31 a.m. |
| PD | Predicate disambiguation | batch_69ef89d5f71881908b9f9d0c8aab278c |
completed | April 27, 2026, 4:07 p.m. |
Created at: April 17, 2026, 3:55 p.m.