Triple
T3147595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syfy |
E65799
|
entity |
| Predicate | notableProgram |
P4
|
FINISHED |
| Object |
Eureka
Eureka is a science fiction television series that follows the quirky residents of a secret high-tech town where brilliant scientists’ experiments frequently go awry.
|
E331099
|
NE FINISHED |
How this triple was built (4 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: Eureka | Statement: [Syfy, notableProgram, Eureka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eureka Context triple: [Syfy, notableProgram, Eureka]
-
A.
Eureka
Eureka is a historic coastal city in Northern California known for its Victorian architecture, maritime heritage, and role as a regional cultural and economic center.
-
B.
Eureka
Eureka is the codename for the Eureka Conference, a World War II meeting between Allied leaders Franklin D. Roosevelt, Winston Churchill, and Joseph Stalin held in Tehran in 1943.
-
C.
Eureka
Eureka is a historic side-wheel paddle steamboat and former ferry now preserved as a museum ship in San Francisco.
-
D.
Old Town Eureka
Old Town Eureka is the historic waterfront district of Eureka, California, known for its well-preserved Victorian architecture, shops, galleries, and cultural attractions.
-
E.
Kay
Kay is a common diminutive or nickname for the given name Catherine.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Eureka Triple: [Syfy, notableProgram, Eureka]
Generated description
Eureka is a science fiction television series that follows the quirky residents of a secret high-tech town where brilliant scientists’ experiments frequently go awry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eureka Target entity description: Eureka is a science fiction television series that follows the quirky residents of a secret high-tech town where brilliant scientists’ experiments frequently go awry.
-
A.
Eureka
Eureka is a historic coastal city in Northern California known for its Victorian architecture, maritime heritage, and role as a regional cultural and economic center.
-
B.
Eureka
Eureka is the codename for the Eureka Conference, a World War II meeting between Allied leaders Franklin D. Roosevelt, Winston Churchill, and Joseph Stalin held in Tehran in 1943.
-
C.
Eureka
Eureka is a historic side-wheel paddle steamboat and former ferry now preserved as a museum ship in San Francisco.
-
D.
Old Town Eureka
Old Town Eureka is the historic waterfront district of Eureka, California, known for its well-preserved Victorian architecture, shops, galleries, and cultural attractions.
-
E.
Kay
Kay is a common diminutive or nickname for the given name Catherine.
- F. None of above. chosen
Provenance (5 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada59a54188190a2e020fd4004d734 |
completed | March 8, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b224f53bbc81908416272cd48af69e |
completed | March 12, 2026, 2:29 a.m. |
| NEDg | Description generation | batch_69b225896c4c81909e875a2d357e7bc5 |
completed | March 12, 2026, 2:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b225fef06081908dcd8201def1ad95 |
completed | March 12, 2026, 2:33 a.m. |
Created at: March 8, 2026, 3:05 p.m.