Triple
T30605411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finn McMissile |
E779026
|
entity |
| Predicate | hasMissionInCars2 |
P153594
|
FINISHED |
| Object | investigate the Lemons conspiracy |
—
|
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: investigate the Lemons conspiracy | Statement: [Finn McMissile, hasMissionInCars2, investigate the Lemons conspiracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMissionInCars2 Context triple: [Finn McMissile, hasMissionInCars2, investigate the Lemons conspiracy]
-
A.
hasMissionIn
Indicates that an entity carries out, undertakes, or is assigned a mission within a specified location or region.
-
B.
containsMission
Indicates that one entity includes or encompasses a mission as part of its contents, scope, or responsibilities.
-
C.
hasMissionTo
chosen
Indicates that an entity is assigned or dedicated to carrying out a specific mission, task, or purpose related to another entity or objective.
-
D.
hasMissionSystem
Indicates that an entity is equipped with or associated with a specific mission-related system or subsystem.
-
E.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
- F. None of above.
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_69f224a21fc08190abd9d8dd9eb6bb4c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
Created at: April 29, 2026, 8:25 p.m.