Triple
T8928342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SODO Station |
E212590
|
entity |
| Predicate | servesNeighborhood |
P82
|
FINISHED |
| Object | SoDo |
E52121
|
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: SoDo | Statement: [SODO Station, servesNeighborhood, SoDo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SoDo Context triple: [SODO Station, servesNeighborhood, SoDo]
-
A.
SoDo
chosen
SoDo is a neighborhood and industrial district just south of downtown Seattle, Washington, known for its warehouses, stadiums, and transit connections.
-
B.
Mr. DOB
Mr. DOB is Takashi Murakami’s iconic cartoon-like character and recurring motif that blends Japanese pop culture with fine art in his Superflat style.
-
C.
Sozh
The Sozh is a major river in Eastern Europe that flows through Russia, Belarus, and Ukraine before joining the Dnieper.
-
D.
Sooley
Sooley is a novel by John Grisham that follows a young South Sudanese basketball player whose extraordinary talent offers a path out of war-torn hardship.
-
E.
Sochalien
Sochalien is the French demonym for an inhabitant or native of the town of Sochaux in eastern France.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6672af10819084a6e50f0302f732 |
completed | April 1, 2026, 12:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdb856560819085132abe9ef94819 |
completed | April 3, 2026, 3:23 p.m. |
Created at: March 30, 2026, 6:57 p.m.