Triple
T6521153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | P. G. Wodehouse universe |
E151184
|
entity |
| Predicate | includesSeries |
P1393
|
FINISHED |
| Object | Drones Club stories |
E145683
|
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: Drones Club stories | Statement: [P. G. Wodehouse universe, includesSeries, Drones Club stories]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drones Club stories Context triple: [P. G. Wodehouse universe, includesSeries, Drones Club stories]
-
A.
Drones Club stories
chosen
The Drones Club stories are a series of humorous tales by P. G. Wodehouse centered on the misadventures of idle young London clubmen, including recurring characters like Bertie Wooster.
-
B.
Drone
"Drone" is a song by the American rock band Alice in Chains from their album "Rainier Fog."
-
C.
Drone Mimic
Drone Mimic is a type of Mimic creature that disguises itself as a drone to deceive and ambush unsuspecting targets.
-
D.
DJI Agras
DJI Agras is a series of agricultural drones designed for tasks like crop spraying, seeding, and precision farming.
-
E.
AerClub
AerClub is the loyalty and frequent flyer program of Aer Lingus, offering members points, tier benefits, and rewards for their travel with the airline and its partners.
- 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ad9431f081909b14b3df3414a55f |
completed | March 27, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cb6f934481908a95d7424aa23414 |
completed | March 27, 2026, 6:24 p.m. |
Created at: March 27, 2026, 1:45 p.m.