Triple
T19279261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North West Delhi district |
E482142
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Model Town |
—
|
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: Model Town | Statement: [North West Delhi district, hasSettlement, Model Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Model Town Context triple: [North West Delhi district, hasSettlement, Model Town]
-
A.
Model Town
chosen
Model Town is a residential neighborhood in North Delhi, India, known for its planned layout and connectivity via the Delhi Metro.
-
B.
Toy Town
Toy Town is the colorful, whimsical village setting in Enid Blyton’s Noddy stories, inhabited by living toys and other playful characters.
-
C.
Mytown
Mytown was an Irish boy band from the late 1990s that featured future The Script frontman Danny O’Donoghue.
-
D.
The Model City
The Model City is the nickname of Anniston, Alabama, reflecting its origins as a carefully planned industrial community in the late 19th century.
-
E.
Modelland
Modelland is a young adult fantasy novel by supermodel Tyra Banks that satirically explores the world of modeling through a magical, dystopian academy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbbf817c819098745ed365cda4a9 |
completed | April 20, 2026, 10:11 a.m. |
Created at: April 10, 2026, 1:30 p.m.