Triple
T800876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luzon |
E17124
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Angeles City |
E104973
|
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: Angeles City | Statement: [Luzon, containsCity, Angeles City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angeles City Context triple: [Luzon, containsCity, Angeles City]
-
A.
Angeles City
chosen
Angeles City is a highly urbanized city in the Philippines’ Pampanga province, known as a commercial and cultural hub in Central Luzon.
-
B.
Long Beach
Long Beach is a coastal city in Southern California known for its busy port, waterfront attractions, and diverse urban community within the Los Angeles metropolitan area.
-
C.
Anaheim
Anaheim is a major city in Orange County, California, best known as the home of the Disneyland Resort and a significant hub for tourism and entertainment in the region.
-
D.
Los Angeles
Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
-
E.
San Diego
San Diego is a large coastal city in Southern California known for its mild climate, beaches, naval base, and proximity to the Mexican border.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7cc75e88190bd35aabe51051b51 |
completed | March 1, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c70e6eb48190b019759cd656e629 |
completed | March 4, 2026, 5:45 a.m. |
Created at: March 1, 2026, 7:38 p.m.