Triple
T13903844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Financial Street Subdistrict |
E334293
|
entity |
| Predicate | administrativeLevelWithinCity |
P80007
|
FINISHED |
| Object | township-level division |
—
|
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: township-level division | Statement: [Financial Street Subdistrict, administrativeLevelWithinCity, township-level division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administrativeLevelWithinCity Context triple: [Financial Street Subdistrict, administrativeLevelWithinCity, township-level division]
-
A.
cityDistrictLevel
Indicates that one administrative unit is a district-level subdivision within a given city in the territorial hierarchy.
-
B.
cityLevel
Indicates the administrative or hierarchical rank of a city within a broader regional or national structure.
-
C.
isPartOfAdministrativeLevel
Indicates that one administrative unit is contained within or belongs to a higher-level administrative division in a governance hierarchy.
-
D.
hasMunicipalLevel
chosen
Indicates that an entity is associated with a specific level or tier within a municipal (local government) hierarchy.
-
E.
isInCity
Indicates that one entity is located within the geographical boundaries of a specified city.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25db1e308190aaed6a21e443cc44 |
completed | April 14, 2026, 11:32 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
Created at: April 9, 2026, 10:16 p.m.