Triple
T10025406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Este culture |
E200711
|
entity |
| Predicate | hasMainSite |
P19451
|
FINISHED |
| Object | Oppeano |
E200709
|
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: Oppeano | Statement: [Este culture, hasMainSite, Oppeano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oppeano Context triple: [Este culture, hasMainSite, Oppeano]
-
A.
Oppeano
chosen
Oppeano is a municipality in northern Italy’s Veneto region, historically associated with the ancient Veneti people.
-
B.
Oppau
Oppau is a district of the industrial city of Ludwigshafen am Rhein in Rhineland-Palatinate, Germany, historically known for its large chemical industry facilities.
-
C.
Opolais
Opolais is the surname of Latvian soprano opera singer Kristīne Opolais, renowned for her dramatic roles on major international stages.
-
D.
Opoeteren
Opoeteren is a village in the Belgian province of Limburg that now forms part of the municipality of Maaseik.
-
E.
Opol
Opol is a coastal municipality in Misamis Oriental, Philippines, known for its beaches, eco-tourism attractions, and proximity to Cagayan de Oro City.
- 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_69ca831c45f08190ac1505cc15076608 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcde2009081908eddda7813617df4 |
completed | April 2, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26ac2f14081908deaf3945491af78 |
completed | April 5, 2026, 1:59 p.m. |
Created at: March 30, 2026, 8:53 p.m.