Triple
T10025462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reitia |
E200712
|
entity |
| Predicate | worshipRegion |
P2291
|
FINISHED |
| Object | Ateste |
E200705
|
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: Ateste | Statement: [Reitia, worshipRegion, Ateste]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ateste Context triple: [Reitia, worshipRegion, Ateste]
-
A.
Ateste
chosen
Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
-
B.
Ato
Ato is one of the futuristic, computer-generated "Spheriks" characters who served as an official mascot for the 2002 FIFA World Cup in South Korea and Japan.
-
C.
Assergi
Assergi is a small village in Italy’s Abruzzo region, situated on the slopes of Gran Sasso and known as a gateway to the surrounding national park and mountain research facilities.
-
D.
Ateso
Ateso is a Nilotic language spoken primarily by the Teso people of eastern Uganda and western Kenya.
-
E.
Ate
Ate is a populous district in the eastern part of Lima, Peru, known for its mix of industrial zones, residential areas, and growing commercial activity.
- 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.