Triple
T6702081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oranjesluizen |
E152904
|
entity |
| Predicate | connectsWaterBody |
P6307
|
FINISHED |
| Object | IJ |
E159017
|
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 | Statement: [Oranjesluizen, connectsWaterBody, IJ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IJ Context triple: [Oranjesluizen, connectsWaterBody, IJ]
-
A.
IJ
chosen
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.
-
B.
J
J is a New York City Subway service that runs through Brooklyn and Queens into Manhattan, serving neighborhoods in eastern Brooklyn and southern Queens.
-
C.
J
J is the streetwise, impulsive teenage grandson in the TV series "Animal Kingdom," who becomes entangled in his criminal family's operations.
-
D.
J
J is one of the passenger concourses at Miami International Airport, serving as a terminal area with gates, amenities, and airline operations for departing and arriving flights.
-
E.
JO
JO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Hashemite Kingdom of Jordan.
- 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_69c68807adbc8190b8632df42b39eda0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d0e5eb0c81908c4fa3febd2d23ca |
completed | March 27, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70083e1948190b5ee3fffb9783531 |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:06 p.m.