Triple
T7131406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marina Green |
E166196
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | San Francisco |
E242
|
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: San Francisco | Statement: [Marina Green, hasCity, San Francisco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Francisco Context triple: [Marina Green, hasCity, San Francisco]
-
A.
San Francisco
chosen
San Francisco is a major coastal city in Northern California known for its hilly landscape, iconic Golden Gate Bridge, and role as a historic center of technology and counterculture.
-
B.
San Fransokyo
San Fransokyo is a fictional futuristic hybrid city combining elements of San Francisco and Tokyo, serving as the primary setting of Disney's animated film "Big Hero 6."
-
C.
Sausalito
Sausalito is a picturesque waterfront city in Northern California known for its hillside homes, art galleries, and views of the San Francisco Bay.
-
D.
San Jose
San Jose is a coastal municipality in the Philippine province of Negros Oriental known for its rural communities and proximity to Dumaguete City.
-
E.
San Jose
San Jose is the main town on the island of Tinian in the Northern Mariana Islands, serving as its administrative and population center.
- 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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e66f15b88190bc1fb0f0a8af16a6 |
completed | March 27, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ad7862f081908b53778b8fc4ad4b |
completed | March 28, 2026, 10:29 a.m. |
Created at: March 27, 2026, 2:44 p.m.