Triple
T37551203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onyxia's Lair (level 80 version) |
E933593
|
entity |
| Predicate | mainEncounter |
P15171
|
FINISHED |
| Object | Onyxia encounter |
—
|
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: Onyxia encounter | Statement: [Onyxia's Lair (level 80 version), mainEncounter, Onyxia encounter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainEncounter Context triple: [Onyxia's Lair (level 80 version), mainEncounter, Onyxia encounter]
-
A.
timeframeOfMainEncounter
Indicates the specific period or duration during which the primary encounter or main interaction between the entities takes place.
-
B.
mainBattle
chosen
Indicates that one battle is the primary or most significant engagement associated with a particular conflict, campaign, or entity.
-
C.
settingEncounter
Indicates that an encounter or interaction is taking place within a particular setting or environment.
-
D.
encountersCharacter
Indicates that one character comes into contact with or meets another character, typically within a particular situation or context.
-
E.
protagonistConfronts
Indicates that a main character directly faces and challenges another character, force, or problem in a conflictual encounter.
- 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_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:17 p.m.