Triple
T8449649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Orange |
E199768
|
entity |
| Predicate | reasonForKillingMrBlonde |
P34163
|
FINISHED |
| Object | to save the kidnapped police officer |
—
|
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: to save the kidnapped police officer | Statement: [Mr. Orange, reasonForKillingMrBlonde, to save the kidnapped police officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForKillingMrBlonde Context triple: [Mr. Orange, reasonForKillingMrBlonde, to save the kidnapped police officer]
-
A.
reasonForMurder
chosen
Indicates the motive or underlying cause that led someone to commit a murder.
-
B.
allegedToHaveKilled
Indicates that one entity is claimed or accused, but not proven, to have killed another entity.
-
C.
revealsMurderTo
Indicates that one entity discloses information about a murder to another entity.
-
D.
reasonForConviction
Indicates the specific offense or legal basis for which an individual was found guilty or convicted.
-
E.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44707b88190b3d8b30c45ef4496 |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.