Triple
T15080146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geoffrey Lewis |
E380117
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Blueberry
Blueberry is a Western comic book series co-created by French artist Jean Giraud (Moebius), following the adventures of antihero cavalry officer Mike Blueberry in the American Old West.
|
E1136403
|
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: Blueberry | Statement: [Geoffrey Lewis, notableWork, Blueberry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blueberry Context triple: [Geoffrey Lewis, notableWork, Blueberry]
-
A.
Blueberry
Blueberry is a translucent light-blue color variant famously used on Apple’s early iMac G3 computers.
-
B.
Blueberries
"Blueberries" is a poem by Robert Frost that vividly portrays rural life and the labor of berry-picking in New England.
-
C.
Berry
Berry is a small historic town on the South Coast of New South Wales, Australia, known for its rural charm, heritage buildings, and popular weekend tourism.
-
D.
Berry
Berry is a historic province in central France known for its rural landscapes, medieval heritage, and traditional French culture.
-
E.
Berry
Berry is a common English surname borne by numerous individuals across various fields, including sports, politics, and the arts.
- 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: Blueberry Triple: [Geoffrey Lewis, notableWork, Blueberry]
Generated description
Blueberry is a Western comic book series co-created by French artist Jean Giraud (Moebius), following the adventures of antihero cavalry officer Mike Blueberry in the American Old West.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Blueberry Target entity description: Blueberry is a Western comic book series co-created by French artist Jean Giraud (Moebius), following the adventures of antihero cavalry officer Mike Blueberry in the American Old West.
-
A.
Blueberry
Blueberry is a translucent light-blue color variant famously used on Apple’s early iMac G3 computers.
-
B.
Blueberries
"Blueberries" is a poem by Robert Frost that vividly portrays rural life and the labor of berry-picking in New England.
-
C.
Berry
Berry is a small historic town on the South Coast of New South Wales, Australia, known for its rural charm, heritage buildings, and popular weekend tourism.
-
D.
Berry
Berry is a historic province in central France known for its rural landscapes, medieval heritage, and traditional French culture.
-
E.
Berry
Berry is a common English surname borne by numerous individuals across various fields, including sports, politics, and the arts.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff80008c88190840f94222f867478 |
completed | April 15, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae15d6308190a62b4f66c550db04 |
completed | May 9, 2026, 3:46 a.m. |
| NEDg | Description generation | batch_69feaf8e1b508190b0b5ceb64d44fad6 |
completed | May 9, 2026, 3:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feb038065c8190b60266644db64092 |
completed | May 9, 2026, 3:55 a.m. |
Created at: April 10, 2026, 3:03 a.m.