Triple
T24614929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ice Cream Man |
E609226
|
entity |
| Predicate | hasKillerWeapon |
P156760
|
FINISHED |
| Object | ice cream making tools |
—
|
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: ice cream making tools | Statement: [Ice Cream Man, hasKillerWeapon, ice cream making tools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKillerWeapon Context triple: [Ice Cream Man, hasKillerWeapon, ice cream making tools]
-
A.
hasKiller
Indicates that one entity is the killer or cause of death of another entity.
-
B.
hasKillerType
Indicates a relationship where an entity is associated with a specific type or category of killer.
-
C.
hasKillerDoll
Indicates that an entity possesses, is associated with, or is responsible for a doll characterized as a killer.
-
D.
weaponUsedIn
Indicates that a particular weapon is employed or involved in carrying out a specific event or action.
-
E.
weaponUsedAgainst
Indicates that a particular weapon or instrument is employed in an act of aggression, attack, or harm directed toward a specific target or entity.
- 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_69e2c4d1140081909c58667bf68f80c3 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:31 a.m.