Triple
T13893844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rokin tram stop |
E334037
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Dam Square |
E10692
|
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: Dam Square | Statement: [Rokin tram stop, near, Dam Square]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dam Square Context triple: [Rokin tram stop, near, Dam Square]
-
A.
Dam Square
chosen
Dam Square is the historic central square of Amsterdam, known as a major public gathering place surrounded by notable buildings such as the Royal Palace and the National Monument.
-
B.
Dock Square
Dock Square is the central, historic shopping and dining district of Kennebunkport, Maine, known for its waterfront charm and tourist-friendly boutiques, galleries, and restaurants.
-
C.
Maritime Square
Maritime Square is a major shopping mall and transport hub located on Tsing Yi Island in Hong Kong.
-
D.
Casino Square
Casino Square is a famous, high-profile section of the Monte Carlo street circuit, known for its glamorous setting amid luxury casinos and hotels during the Monaco Grand Prix.
-
E.
Telfair Square
Telfair Square is one of Savannah, Georgia’s historic public squares, known for its landscaped green space and proximity to notable cultural institutions.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a741908190bdf46d76c5f1411a |
completed | April 14, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce7419cc81909488871c16d6b356 |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 10:15 p.m.