Triple
T7036596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Givat Ram |
E163399
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Government Quarter |
E121376
|
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: Government Quarter | Statement: [Givat Ram, adjacentTo, Government Quarter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Government Quarter Context triple: [Givat Ram, adjacentTo, Government Quarter]
-
A.
the Government Quarter
chosen
The Government Quarter is the central complex of Norwegian government buildings in Oslo that houses key ministries and administrative offices.
-
B.
Civic Center
Civic Center is a government and administrative district in Lower Manhattan known for its concentration of courthouses and municipal buildings.
-
C.
Government Center area
The Government Center area is a prominent civic and administrative district in downtown Boston known for its cluster of government buildings and public plazas.
-
D.
Museum District
The Museum District is a cultural neighborhood in Houston, Texas, known for its high concentration of museums, galleries, and cultural institutions.
-
E.
Maritime Quarter
Maritime Quarter is a waterfront district in Swansea, Wales, known for its marina, residential developments, and cultural attractions near the city center.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e220508c8190b8950cf38280b8c2 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775a6e1a08190af7d121cb854118e |
completed | March 28, 2026, 6:31 a.m. |
Created at: March 27, 2026, 2:36 p.m.