Triple
T20864148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauro |
E513705
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Lauro |
—
|
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: Lauro | Statement: [Lauro, hasName, Lauro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauro Context triple: [Lauro, hasName, Lauro]
-
A.
Lauro
chosen
Lauro is a municipality that serves as its own administrative center, indicating that the town and its governing seat share the same name.
-
B.
Tamboril
Tamboril is a municipality in the Dominican Republic’s Santiago Province, known for its cigar production and proximity to the city of Santiago de los Caballeros.
-
C.
Lapa
Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
-
D.
Lapa
Lapa is a municipality in the state of Paraná, Brazil, known for its historical architecture and role in the Federalist Revolution.
-
E.
Quintia
Quintia was a Roman noblewoman of the early Imperial period, known primarily as the mother of the senator and consul Gaius Asinius Gallus Saloninus.
- 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_69e0b4f5b01081909452f654d2fc3f50 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c45e51f08190ac1ff59280ad741b |
completed | April 21, 2026, 12:27 a.m. |
Created at: April 16, 2026, 12:44 p.m.