Triple
T5170372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Firebaugh |
E116661
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Los Banos |
E498326
|
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: Los Banos | Statement: [Firebaugh, near, Los Banos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Los Banos Context triple: [Firebaugh, near, Los Banos]
-
A.
Los Banos
chosen
Los Banos is a small agricultural city in California’s San Joaquin Valley, known for farming, wetlands, and its role as a growing commuter community.
-
B.
Los Baños
Los Baños is a municipality in the Philippines known as a major center for agricultural research and education, particularly in rice science.
-
C.
Las Peñas
Las Peñas is a historic, colorful riverside neighborhood in Guayaquil, Ecuador, known for its colonial-era houses, art galleries, and panoramic views from the Santa Ana hill.
-
D.
Las Cañitas
Las Cañitas is a trendy, upscale neighborhood in Buenos Aires known for its vibrant nightlife, fashionable restaurants, and proximity to the city’s polo fields.
-
E.
San Manuel
San Manuel is a municipality in the province of Tarlac in the Philippines, known primarily as an agricultural community.
- 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd794f44248190a3a90c92208104a7 |
completed | March 20, 2026, 4:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed9439ec881909021973aa5395e4f |
completed | March 21, 2026, 5:45 p.m. |
Created at: March 20, 2026, 1:45 p.m.