Triple
T17257097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raseiniai District Municipality |
E418909
|
entity |
| Predicate | hasSeat |
P3522
|
FINISHED |
| Object | Raseiniai |
E412905
|
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: Raseiniai | Statement: [Raseiniai District Municipality, hasSeat, Raseiniai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raseiniai Context triple: [Raseiniai District Municipality, hasSeat, Raseiniai]
-
A.
Raseiniai
chosen
Raseiniai is a historic town in central Lithuania known for its role in regional trade and its cultural heritage within Kaunas County.
-
B.
Pardais
Pardais is a civil parish in the municipality of Vila Viçosa, in Portugal’s Alentejo region.
-
C.
Ruklys
Ruklys was a son of King Mindaugas of Lithuania, known primarily from medieval historical records of the Lithuanian royal family.
-
D.
Sudeikis
Sudeikis is the surname of American actor, comedian, and writer Jason Sudeikis, known for his work on Saturday Night Live and the series Ted Lasso.
-
E.
Kaišiadorys
Kaišiadorys is a small Lithuanian town known as an important railway junction and administrative center in central Lithuania.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6dde4881908e7fc01fd5364616 |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0179445cac8190833eb7cd879a93bd |
completed | May 11, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:39 a.m.