Triple
T2358488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flying Pencil |
E47212
|
entity |
| Predicate | nicknamedFor |
P38200
|
FINISHED |
| Object | slender fuselage shape |
—
|
LITERAL 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: slender fuselage shape | Statement: [Flying Pencil, nicknamedFor, slender fuselage shape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknamedFor Context triple: [Flying Pencil, nicknamedFor, slender fuselage shape]
-
A.
notableNickname
Indicates that one entity is a well-known or widely recognized nickname or moniker for another entity.
-
B.
isOfficialNicknameOf
Indicates that one name is the formally recognized nickname or informal moniker used to refer to another entity.
-
C.
touristRegionNickname
Indicates that a tourist region is known by a particular informal or colloquial nickname.
-
D.
notableTeamNickname
Indicates that a team is commonly known by a particular nickname that is notable or widely recognized.
-
E.
athleticsNickname
Indicates the commonly used nickname or moniker for an entity’s athletics team or sports program.
- F. None of above. chosen
Provenance (4 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_69a88a1a4a6081908645b0f2914521ab |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc71f767481908dfa9be209ea3c5a |
completed | March 7, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69abc599b92c819093d9e15d4437705d |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6a85e2c8190afec217ff29476be |
completed | March 7, 2026, 6:33 a.m. |
Created at: March 4, 2026, 7:55 p.m.