Triple
T3121223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Levine |
E65187
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Bridge |
E161470
|
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: The Bridge | Statement: [Ted Levine, notableWork, The Bridge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Bridge Context triple: [Ted Levine, notableWork, The Bridge]
-
A.
The Bridge
chosen
The Bridge is an American crime drama television series in which Diane Kruger stars as a brilliant but socially awkward detective investigating cross-border murders on the U.S.–Mexico frontier.
-
B.
City of Bridges
City of Bridges is a nickname for Pittsburgh, Pennsylvania, highlighting its unusually large number of river-spanning bridges and distinctive topography.
-
C.
Bridge
Bridge is a structural design pattern that decouples an abstraction from its implementation so that the two can vary independently.
-
D.
Bridge at Grave
Bridge at Grave is a strategically significant road bridge over the Maas River near the Dutch town of Grave, known for its role in Operation Market Garden during World War II.
-
E.
Bridge (formerly)
Bridge (formerly) is a corporate learning and employee development platform that helps organizations deliver training, track performance, and improve workforce engagement.
- 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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5295cd481908d52e165538c67fa |
completed | March 8, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f6bc644819093a7cab7220f4ca0 |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.