Triple
T28840232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerbangkertosusila region |
E728292
|
entity |
| Predicate | isPlanningConceptFor |
P83760
|
FINISHED |
| Object | Greater Surabaya metropolitan area |
—
|
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: Greater Surabaya metropolitan area | Statement: [Gerbangkertosusila region, isPlanningConceptFor, Greater Surabaya metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPlanningConceptFor Context triple: [Gerbangkertosusila region, isPlanningConceptFor, Greater Surabaya metropolitan area]
-
A.
hasPlanningConcept
Indicates that an entity is associated with, defined by, or governed by a particular planning-related concept or framework.
-
B.
plannedIn
Indicates that an event, activity, or process is scheduled or arranged to occur within a specific context, timeframe, or plan.
-
C.
hasPlanningType
Indicates that an entity is associated with a specific category or type used for planning or scheduling purposes.
-
D.
plannedUnder
Indicates that one entity has been scheduled, organized, or arranged to occur within the scope, authority, or framework of another entity.
-
E.
conceptualizedFor
chosen
Indicates that one entity has been conceived, designed, or mentally framed specifically for use, application, or relevance to another entity.
- 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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 6:40 a.m.