Triple
T37552975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Light’s Vengeance |
E933629
|
entity |
| Predicate | timelineAssociation |
P140457
|
FINISHED |
| Object | events preceding Arthas’s corruption |
—
|
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: events preceding Arthas’s corruption | Statement: [Light’s Vengeance, timelineAssociation, events preceding Arthas’s corruption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timelineAssociation Context triple: [Light’s Vengeance, timelineAssociation, events preceding Arthas’s corruption]
-
A.
periodAssociatedWith
chosen
Indicates an association or linkage between something and a specific time period or temporal span.
-
B.
trailAssociation
Indicates an associative relationship between entities where one is contextually or functionally linked to a trail (such as being located on, connected to, or part of that trail).
-
C.
sceneAssociation
Indicates a contextual or thematic relationship linking entities that co-occur or interact within the same scene.
-
D.
associatedThrough
Indicates that two entities are connected or related to each other by means of a specified intermediary, context, or linkage.
-
E.
trackRelationship
Indicates a connection in which one entity monitors, follows, or keeps a record of another entity’s state, behavior, or changes over time.
- 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_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.