Triple
T12671378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arconia apartment building |
E302688
|
entity |
| Predicate | hasNotableEventTypeInStory |
P87547
|
FINISHED |
| Object | murder investigations |
—
|
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: murder investigations | Statement: [Arconia apartment building, hasNotableEventTypeInStory, murder investigations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableEventTypeInStory Context triple: [Arconia apartment building, hasNotableEventTypeInStory, murder investigations]
-
A.
hasInfluentialStory
Indicates that one entity possesses or is associated with a story that significantly shapes, impacts, or guides the beliefs, actions, or development of another entity.
-
B.
hasNotablePersonEvent
Indicates that there exists a significant event in which the person plays a notable or central role.
-
C.
notableRecentStoryline
Indicates that there is a particularly significant or newsworthy recent sequence of events or developments involving the subject.
-
D.
hasThemeInStory
Indicates that a particular theme is present or plays a significant role within a given story.
-
E.
hasFictionalEventType
chosen
Indicates that something is associated with, characterized by, or classified under a particular type or category of fictional event.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.