Triple
T9110523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood Hills |
E218588
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Universal City |
E102732
|
NE 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: Universal City | Statement: [Hollywood Hills, borders, Universal City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Universal City Context triple: [Hollywood Hills, borders, Universal City]
-
A.
Universal City
Universal City is a suburban community in the San Antonio metropolitan area of south-central Texas, known for its proximity to Randolph Air Force Base.
-
B.
Universal City, California
chosen
Universal City, California is an unincorporated community in Los Angeles County best known as the home of the Universal Studios film studio and theme park complex.
-
C.
Universal City Station
Universal City Station is a railway station in Osaka, Japan, serving as the primary train access point for visitors to Universal Studios Japan and the surrounding entertainment district.
-
D.
Hollywood
Hollywood is a coastal city in southeastern Florida known for its beaches, boardwalk, and proximity to Miami.
-
E.
Hollywood
Hollywood is a residential neighborhood in the city of College Park, Maryland, known for its suburban character and proximity to the University of Maryland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca847102881908f9d86ce9883fb1a |
completed | April 1, 2026, 5:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05449101481908c71475acf59b33c |
completed | April 3, 2026, 11:59 p.m. |
Created at: March 30, 2026, 7:16 p.m.