Triple
T12592724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sangenjaya |
E300644
|
entity |
| Predicate | hasTypeOfUrbanForm |
P90675
|
FINISHED |
| Object | mixed-use neighborhood |
—
|
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: mixed-use neighborhood | Statement: [Sangenjaya, hasTypeOfUrbanForm, mixed-use neighborhood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfUrbanForm Context triple: [Sangenjaya, hasTypeOfUrbanForm, mixed-use neighborhood]
-
A.
containsUrbanForm
Indicates that one entity spatially includes or encompasses an urban form or built-up area within its extent.
-
B.
isUrbanForm
Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
-
C.
hasUrbanLayoutType
chosen
Indicates that an entity possesses or is characterized by a specific type or pattern of urban spatial layout.
-
D.
isUrbanAreaOfType
Indicates that a given area is classified as belonging to a specific type or category of urban area (e.g., city, town, suburb).
-
E.
hasUrbanClassification
Indicates that an entity is assigned a specific urban status or category within a defined classification system.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5:07 p.m.