Triple
T15621240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marin Peninsula |
E375558
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | San Rafael |
E171903
|
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 Rafael | Statement: [Marin Peninsula, contains, San Rafael]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Rafael Context triple: [Marin Peninsula, contains, San Rafael]
-
A.
San Rafael
San Rafael is a major city in Argentina’s Mendoza Province, known for its wine production, agriculture, and proximity to popular Andean tourist attractions.
-
B.
San Rafael
chosen
San Rafael is a city in the North Bay region of the San Francisco Bay Area in California, known for its historic downtown and role as a cultural and economic hub of Marin County.
-
C.
San Rafael
San Rafael is a small rural municipality in Chile’s Maule Region, known for its agricultural activities and proximity to the regional capital, Talca.
-
D.
San Rafael
San Rafael is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and growing suburban communities.
-
E.
Santa Cruz
Santa Cruz is a coastal municipality in the Philippine island province of Marinduque known for its fishing communities and rural island-barangays.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9a95f08190b0013ba1428849d3 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff997b9c9081908f6a68e28a50a359 |
completed | May 9, 2026, 8:30 p.m. |
Created at: April 10, 2026, 4:13 a.m.