Triple
T4934943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innsbruck |
E110788
|
entity |
| Predicate | twinCity |
P1072
|
FINISHED |
| Object | Laibin |
E428484
|
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: Laibin | Statement: [Innsbruck, twinCity, Laibin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laibin Context triple: [Innsbruck, twinCity, Laibin]
-
A.
Laibin
chosen
Laibin is a prefecture-level city in south-central China known for its role as a regional transportation hub and its mix of industrial and agricultural development.
-
B.
Ljabru
Ljabru is a neighborhood in Oslo, Norway, known as the southeastern terminus of one of the city’s tram lines.
-
C.
Lindinis
Lindinis is the Roman-era name for the town now known as Ilchester in Somerset, England, which served as an important settlement in Roman Britain.
-
D.
Priebus
Priebus is the surname of Reince Priebus, an American attorney and political operative who served as White House Chief of Staff under President Donald Trump.
-
E.
Liuboml
Liuboml is a small historic town in western Ukraine near the Polish border, known for its medieval roots and multicultural heritage.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706825188190b854dca5ca2f9db6 |
completed | March 20, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77b74c748190a995a26f45b79ee9 |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:30 p.m.