Triple
T6329534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zadar Channel |
E141942
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Bibinje |
E573940
|
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: Bibinje | Statement: [Zadar Channel, hasNearbySettlement, Bibinje]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bibinje Context triple: [Zadar Channel, hasNearbySettlement, Bibinje]
-
A.
Bibinje
chosen
Bibinje is a coastal village and popular tourist destination on the Adriatic Sea in Croatia, located just southeast of the city of Zadar.
-
B.
Bibirevo
Bibirevo is a Moscow Metro station serving the Bibirevo District in the north of the city.
-
C.
Bednja
Bednja is a river in northern Croatia that flows through the Zagorje region before joining the Drava River.
-
D.
Paju
Paju is a city in South Korea near the Demilitarized Zone, known for its historical sites, cultural complexes, and role as a border hub with North Korea.
-
E.
Kameçvara
Kameçvara was a prominent king of the medieval Javanese Kediri Kingdom, remembered for his prosperous reign and association with the classic romance tale of Panji.
- 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_69c008d201748190917e69c41ba3f978 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0651334c08190a9514faa36e7812d |
completed | March 22, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c604154a1c8190b09e74cea2a18624 |
completed | March 27, 2026, 4:14 a.m. |
Created at: March 22, 2026, 4:30 p.m.