Triple
T9153415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luwan District |
E219645
|
entity |
| Predicate | cityTierContext |
P87044
|
FINISHED |
| Object | central urban district of Shanghai |
—
|
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: central urban district of Shanghai | Statement: [Luwan District, cityTierContext, central urban district of Shanghai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityTierContext Context triple: [Luwan District, cityTierContext, central urban district of Shanghai]
-
A.
cityLevel
Indicates the administrative or hierarchical rank of a city within a broader regional or national structure.
-
B.
urbanizationLevel
Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
-
C.
cityDistrictLevel
Indicates that one administrative unit is a district-level subdivision within a given city in the territorial hierarchy.
-
D.
hasCityRank
Indicates that a city holds a particular rank or position within a defined ordering or hierarchy (such as size, importance, or administrative level).
-
E.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
- F. None of above. chosen
Provenance (4 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_69ca83e25418819093c6503deeaf30de |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca96e323881909cbf4d6708f24f79 |
completed | April 1, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69cc6603ce8c8190bf6e8d6754bdec54 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3d230881909635b2ccea35cedb |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:20 p.m.