Triple
T7372521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shasta College |
E170042
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Redding |
E27620
|
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: Redding | Statement: [Shasta College, city, Redding]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Redding Context triple: [Shasta College, city, Redding]
-
A.
Redding
Redding is a village in central Scotland, situated within the Falkirk council area and historically associated with coal mining.
-
B.
Redding
chosen
Redding is a mid-sized city in Northern California known as a regional hub for outdoor recreation, with access to Shasta Lake, the Sacramento River, and nearby national forests.
-
C.
Redding
Redding was the former name of Elizabeth City, a historic riverfront community in northeastern North Carolina.
-
D.
Modesto
Modesto is a mid-sized city in California’s Central Valley known for its agricultural economy, historic connection to the railroads, and as the hometown setting inspiration for George Lucas’s film "American Graffiti."
-
E.
Modesto
Modesto was a prominent Spanish Republican military commander during the Spanish Civil War.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f18451d88190ad4a2674279bb703 |
completed | March 27, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802caa9988190bdc0ed5d5dd15979 |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:07 p.m.