Triple
T6103737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angel Stadium of Anaheim |
E136065
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Anaheim |
E34531
|
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: Anaheim | Statement: [Angel Stadium of Anaheim, city, Anaheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anaheim Context triple: [Angel Stadium of Anaheim, city, Anaheim]
-
A.
Anaheim
chosen
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.
-
B.
Irvine
Irvine is a master-planned city in Orange County, California, known for its affluent residential communities, strong public schools, and concentration of technology and education industries.
-
C.
Irvine
Irvine is a coastal town in North Ayrshire, Scotland, known historically as a royal burgh and port on the Firth of Clyde.
-
D.
Huntington Beach
Huntington Beach is a coastal city in Southern California known for its long sandy beaches, surf culture, and vibrant seaside community.
-
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_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3dbc6c8190b9e3d81e6ca9eeb8 |
completed | March 22, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1359334c081909653603633ba9c06 |
completed | March 23, 2026, 12:44 p.m. |
Created at: March 22, 2026, 4:13 p.m.