Triple
T2224021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amsterdam North |
E48606
|
entity |
| Predicate | locatedAcross |
P382
|
FINISHED |
| Object | IJ Bay |
E3945
|
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: IJ Bay | Statement: [Amsterdam North, locatedAcross, IJ Bay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IJ Bay Context triple: [Amsterdam North, locatedAcross, IJ Bay]
-
A.
IJ Bay
chosen
IJ Bay is a body of water in the Netherlands that forms a key waterfront and harbor area for the city of Amsterdam.
-
B.
IJ
The IJ is a body of water in Amsterdam that serves as a key waterway for transport and shipping, separating the city center from Amsterdam-Noord.
-
C.
Illana Bay
Illana Bay is a coastal inlet in the southern Philippines that served as a key Allied amphibious landing area during the World War II campaign to liberate Mindanao.
-
D.
Osan
Osan is a city in Gyeonggi Province, South Korea, known for its proximity to Osan Air Base and its role as a regional transportation and commercial hub.
-
E.
JAX
JAX is a high-performance numerical computing library for Python that combines NumPy-like APIs with automatic differentiation and just-in-time compilation, widely used for machine learning and scientific computing.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03ec3788190b5ae32201364f7ab |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6562c9448190b53c068c900bf0bf |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:47 p.m.