Triple
T15754625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montebello, California |
E381935
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object | Rio Hondo |
E367080
|
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: Rio Hondo | Statement: [Montebello, California, locatedOn, Rio Hondo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio Hondo Context triple: [Montebello, California, locatedOn, Rio Hondo]
-
A.
Rio Hondo
chosen
Rio Hondo is a major urban stream in Los Angeles County that serves as a key tributary to the Los Angeles River and plays an important role in regional flood control and water management.
-
B.
Rio Largo
Rio Largo is a municipality in the Brazilian state of Alagoas, known for its role in the region’s sugarcane industry and proximity to the state capital, Maceió.
-
C.
Rio Hato
Rio Hato is a coastal area in Panama known for its airfield, which was a key target during the U.S. invasion of Panama in Operation Just Cause.
-
D.
Rio Bonito
Rio Bonito is a municipality in the state of Rio de Janeiro, Brazil, known for its Atlantic Forest landscapes and role as a regional agricultural and service center.
-
E.
La Plata River
La Plata River is a major river in Puerto Rico that flows through several municipalities, including Bayamón, before emptying into the Atlantic Ocean.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05031f6a08190bfb333eced0a59a1 |
completed | April 16, 2026, 2:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff9096d65c81908755cae83cc48e61 |
completed | May 9, 2026, 7:52 p.m. |
Created at: April 10, 2026, 4:47 a.m.