Triple
T20584453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sieradz County |
E505747
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | ESI |
—
|
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: ESI | Statement: [Sieradz County, vehicleRegistrationCode, ESI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ESI Context triple: [Sieradz County, vehicleRegistrationCode, ESI]
-
A.
ESI
chosen
ESI is the vehicle registration code used on car license plates issued in the Sieradz area of Poland.
-
B.
ISI
ISI is an organization that inspects and regulates independent schools to ensure they meet required educational and welfare standards.
-
C.
ISI
ISI (the Institute for Scientific Information) is a pioneering organization in bibliometrics and citation indexing, best known for creating influential tools for tracking and analyzing scientific literature.
-
D.
ISI
ISI is Pakistan’s premier military intelligence agency, responsible for national security intelligence and covert operations.
-
E.
SCImago Research Group
SCImago Research Group is an academic research organization best known for creating bibliometric indicators and journal rankings that analyze and visualize scientific output and impact worldwide.
- 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_69e0b4b9669c8190b8e81fc72817d42c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a975f098819083700593a9fa6cd0 |
completed | April 20, 2026, 10:32 p.m. |
Created at: April 16, 2026, 11:40 a.m.