Triple
T7996510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amsterdam bridge network |
E186139
|
entity |
| Predicate | includesNotableElement |
P11236
|
FINISHED |
| Object | Python Bridge |
E123163
|
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: Python Bridge | Statement: [Amsterdam bridge network, includesNotableElement, Python Bridge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Python Bridge Context triple: [Amsterdam bridge network, includesNotableElement, Python Bridge]
-
A.
Python Bridge
chosen
Python Bridge is a striking red pedestrian and cycle bridge in Amsterdam known for its steep, serpentine design connecting parts of the Eastern Docklands.
-
B.
Jython
Jython is an implementation of the Python programming language that runs on the Java platform and allows seamless integration with Java code and libraries.
-
C.
Pythonidae
Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
-
D.
Python
Python is a monstrous serpent or dragon from Greek mythology, best known for being slain by the god Apollo at Delphi.
-
E.
Python
Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c97968481908d261b3f0bd6b8e6 |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe10d5eb081909f257390094de442 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:17 p.m.