Triple
T12145022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guandu River |
E289294
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Itaguaí |
E874707
|
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: Itaguaí | Statement: [Guandu River, locatedNear, Itaguaí]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Itaguaí Context triple: [Guandu River, locatedNear, Itaguaí]
-
A.
Itaguaí
chosen
Itaguaí is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its major port facilities and heavy industrial and logistics activities.
-
B.
Resende
Resende is a Portuguese municipality in the Douro region, known for its scenic river landscapes and production of cherries and vinho verde.
-
C.
Resende
Resende is a municipality in the state of Rio de Janeiro, Brazil, known as an important industrial and regional center in the southern part of the state.
-
D.
Três Rios
Três Rios is a municipality in the state of Rio de Janeiro, Brazil, known as a regional commercial and logistical hub at the confluence of three rivers.
-
E.
Teresópolis
Teresópolis is a mountainous city in the state of Rio de Janeiro, Brazil, known for its cool climate, natural parks, and role as a popular ecotourism and weekend getaway destination.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915aacaa08190b31f54e230334406 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63ee285208190a0183e30c749f955 |
completed | May 2, 2026, 6:13 p.m. |
Created at: April 8, 2026, 9:49 p.m.