Triple
T17913819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiotari |
E447875
|
entity |
| Predicate | nearbyPlace |
P2064
|
FINISHED |
| Object | Lindos |
—
|
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: Lindos | Statement: [Kiotari, nearbyPlace, Lindos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lindos Context triple: [Kiotari, nearbyPlace, Lindos]
-
A.
Lindos
chosen
Lindos is a historic coastal village on the Greek island of Rhodes, famed for its ancient acropolis, whitewashed houses, and scenic beaches.
-
B.
Hermosa
Hermosa is a municipality in the province of Bataan in the Philippines, known for its agricultural lands and growing industrial and residential developments.
-
C.
Hermosa
Hermosa is a primarily residential neighborhood on Chicago’s Northwest Side known for its diverse community and as the childhood home of Walt Disney.
-
D.
Riviera
Riviera is a distinctive Baume & Mercier luxury sports watch collection known for its bold, angular case design and casual-elegant style.
-
E.
Riviera
Riviera is a television drama series centered on wealth, crime, and intrigue along the glamorous French Riviera.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30461848190b932a45807329216 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 10:20 a.m.