Triple
T13574872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagoya City Transportation Bureau |
E324253
|
entity |
| Predicate | operatesUnderLegalForm |
P96805
|
FINISHED |
| Object | municipal bureau |
—
|
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: municipal bureau | Statement: [Nagoya City Transportation Bureau, operatesUnderLegalForm, municipal bureau]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesUnderLegalForm Context triple: [Nagoya City Transportation Bureau, operatesUnderLegalForm, municipal bureau]
-
A.
hasUnderlyingCompanyLegalForm
Indicates that an entity is associated with, or governed by, a specific underlying legal form of a company.
-
B.
hasLegalStructure
chosen
Indicates that an entity possesses a specific formal legal organization or classification under law.
-
C.
typicalLegalForm
Indicates the standard or commonly used legal organizational form associated with an entity.
-
D.
belongsToCompanyLegalForm
Indicates that an entity is associated with or classified under a specific legal form of a company.
-
E.
legalFormedAs
Indicates that an entity was established or constituted under a specific legal structure or organizational form.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb02b1f108190a12af382d1de70bb |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.