Triple
T23460194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funhalouro |
E568947
|
entity |
| Predicate | administrativeDivisionOf |
P747
|
FINISHED |
| Object | Funhalouro District |
—
|
NE NERFINISHED |
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: Funhalouro District | Statement: [Funhalouro, administrativeDivisionOf, Funhalouro District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Funhalouro District Context triple: [Funhalouro, administrativeDivisionOf, Funhalouro District]
-
A.
Funhalouro District
chosen
Funhalouro District is an administrative district located in Inhambane Province in southern Mozambique.
-
B.
Marcas District
Marcas District is an administrative district located within Acobamba Province in the Huancavelica region of central Peru.
-
C.
Olá District
Olá District is an administrative district in central Panama, located within Coclé Province and comprising several rural communities.
-
D.
Lapa district
Lapa district is a historic neighborhood in central Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic Arcos da Lapa aqueduct.
-
E.
Morumbi district
Morumbi district is an affluent residential and commercial neighborhood in São Paulo, Brazil, known for its upscale housing, shopping centers, and major sports venues.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a69afba88190b1b1dd27d331309f |
completed | April 29, 2026, 6:35 a.m. |
Created at: April 17, 2026, 5:53 p.m.