Triple
T17766432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Plata River |
E443517
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Naranjito |
E1081877
|
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: Naranjito | Statement: [La Plata River, flowsThrough, Naranjito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naranjito Context triple: [La Plata River, flowsThrough, Naranjito]
-
A.
Naranjito
Naranjito is a municipality located in the central region of Puerto Rico, known for its mountainous terrain and agricultural traditions.
-
B.
Naranjito
Naranjito is the smiling orange cartoon character that served as the official mascot of the 1982 FIFA World Cup held in Spain.
-
C.
Naranjito
chosen
Naranjito is a town in Ecuador’s Guayas Province known for its agricultural activity, particularly in sugarcane and tropical fruit production.
-
D.
Naranjas
Naranjas is a Cuban baseball team nickname associated with the Villa Clara Naranjas of the Cuban National Series.
-
E.
Blanquita
Blanquita is the namesake figure—likely an influential woman or performer—after whom Mexico City’s historic Teatro Blanquita was named.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485fc03e48190a8044e1b40f66f20 |
completed | April 19, 2026, 7:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02efc14808819099ecbb8a752aff24 |
completed | May 12, 2026, 9:15 a.m. |
Created at: April 10, 2026, 10:11 a.m.