Triple
T28294585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shizhen |
E713524
|
entity |
| Predicate | associatedGeographicRegion |
P194797
|
FINISHED |
| Object | China |
—
|
NE NERFINISHED |
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: China | Statement: [Shizhen, associatedGeographicRegion, China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedGeographicRegion Context triple: [Shizhen, associatedGeographicRegion, China]
-
A.
associatedAdministrativeRegion
Indicates that an entity is linked to, or falls under the jurisdiction of, a particular administrative region.
-
B.
geographicalRegionType
Indicates the specific kind or category of geographical region that an entity belongs to (e.g., continent, country, province, or city).
-
C.
regionallyAssociatedWith
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
D.
associatedRegions
chosen
Indicates that there is a relevant connection or linkage between an entity and one or more geographic or administrative regions.
-
E.
socialRegionFor
Indicates a relationship where a social entity (such as a group, community, or organization) is associated with or operates within a particular geographic or social region.
- 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_69efb524ab688190a1ce7ee7c9520932 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_6a012594c27081908c80f0e0e6010290 |
completed | May 11, 2026, 12:40 a.m. |
| PD | Predicate disambiguation | batch_6a01252350548190b1df9edc9e581e91 |
completed | May 11, 2026, 12:38 a.m. |
Created at: April 27, 2026, 11:31 p.m.