Triple
T1101102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Docklands |
E24381
|
entity |
| Predicate | locatedIn |
P40
|
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: [Western Docklands, locatedIn, IJ Bay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IJ Bay Context triple: [Western Docklands, locatedIn, 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.
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.
-
C.
Weno
Weno is the main urban and commercial center of Chuuk State in the Federated States of Micronesia, known for its lagoon setting and role as a regional hub.
-
D.
The Bay
The Bay is a major Canadian department store chain offering a wide range of fashion, home goods, and accessories.
-
E.
Tenjin
Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c079f48190a0e0ddda182f7a01 |
completed | March 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c47dbf88190a1898d7bda32ecb2 |
completed | March 7, 2026, 4:03 p.m. |
Created at: March 1, 2026, 7:43 p.m.