Triple
T16971693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian cruiser Bayan |
E411698
|
entity |
| Predicate | stationedAt |
P40
|
FINISHED |
| Object | Port Arthur |
E298645
|
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: Port Arthur | Statement: [Russian cruiser Bayan, stationedAt, Port Arthur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Port Arthur Context triple: [Russian cruiser Bayan, stationedAt, Port Arthur]
-
A.
Port Arthur
Port Arthur is an industrial city in southeast Texas known for its major oil refineries and petrochemical facilities along the Gulf Coast.
-
B.
Port Arthur
chosen
Port Arthur is a strategically important ice-free naval port and former fortress city in northeastern China, historically contested by major powers such as Russia and Japan.
-
C.
Port Arthur
Port Arthur is a historic former penal settlement and popular heritage tourism site on Tasmania’s Tasman Peninsula in Australia.
-
D.
Portsea
Portsea is an affluent coastal resort town on Victoria’s Mornington Peninsula, known for its beaches, holiday homes, and proximity to Port Phillip Heads.
-
E.
Portsea
Portsea is a district of the city of Portsmouth on the south coast of England, historically known for its naval connections and dense urban development.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0ad04ac81909a11b45be567613a |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d471d4248190acf40b6c11926a65 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.