Triple
T32239681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BIN |
E823573
|
entity |
| Predicate | registrationDistrictType |
P80652
|
FINISHED |
| Object | town |
—
|
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: town | Statement: [BIN, registrationDistrictType, town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registrationDistrictType Context triple: [BIN, registrationDistrictType, town]
-
A.
typeOfDistrict
chosen
Indicates the specific category or classification to which a given district belongs.
-
B.
cityDistrictType
Indicates the type or classification of a city district within an urban or administrative structure.
-
C.
identifiesRegistrationDistrict
Indicates that one entity specifies or designates the registration district to which another entity belongs or is associated.
-
D.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
E.
governmentalDistrictOf
Indicates that a governmental district is the administrative district to which a given entity belongs or in which it is located.
- 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_69f3490c140481908ed53b98b561eaa1 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bc2f34f88190ae24a9bba5e6c8ec |
completed | May 3, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:39 a.m.