Triple
T21655875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cypress County |
E534463
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Irvine
Irvine is a small hamlet in southeastern Alberta, Canada, situated along the Trans-Canada Highway east of Medicine Hat.
|
E1497980
|
NE FINISHED |
How this triple was built (4 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: Irvine | Statement: [Cypress County, contains, Irvine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Irvine Context triple: [Cypress County, contains, Irvine]
-
A.
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.
-
B.
Irvine
Irvine is a coastal town in North Ayrshire, Scotland, known historically as a royal burgh and port on the Firth of Clyde.
-
C.
Costa Mesa
Costa Mesa is a city in Orange County, California, known for its major shopping centers, arts and theater district, and proximity to Southern California beaches.
-
D.
El Cajon
El Cajon is a suburban city in Southern California’s East County region, located just east of San Diego.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Irvine Triple: [Cypress County, contains, Irvine]
Generated description
Irvine is a small hamlet in southeastern Alberta, Canada, situated along the Trans-Canada Highway east of Medicine Hat.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Irvine Target entity description: Irvine is a small hamlet in southeastern Alberta, Canada, situated along the Trans-Canada Highway east of Medicine Hat.
-
A.
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.
-
B.
Irvine
Irvine is a coastal town in North Ayrshire, Scotland, known historically as a royal burgh and port on the Firth of Clyde.
-
C.
Costa Mesa
Costa Mesa is a city in Orange County, California, known for its major shopping centers, arts and theater district, and proximity to Southern California beaches.
-
D.
El Cajon
El Cajon is a suburban city in Southern California’s East County region, located just east of San Diego.
-
E.
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.
- F. None of above. chosen
Provenance (5 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef59185b208190a2cf4b8f54a2c231 |
completed | April 27, 2026, 12:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a249caaec81908f811dc53312cf0b |
completed | May 17, 2026, 8:27 p.m. |
| NEDg | Description generation | batch_6a0a27007ed88190a416ccd61d6c042f |
completed | May 17, 2026, 8:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a27630ce08190a885d86bfc6986cf |
completed | May 17, 2026, 8:38 p.m. |
Created at: April 16, 2026, 6:36 p.m.