Triple
T38590029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neltharion's Tear |
E932431
|
entity |
| Predicate | gearCategory |
P191244
|
FINISHED |
| Object | Pre-Ahn'Qiraj caster trinket |
—
|
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: Pre-Ahn'Qiraj caster trinket | Statement: [Neltharion's Tear, gearCategory, Pre-Ahn'Qiraj caster trinket]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gearCategory Context triple: [Neltharion's Tear, gearCategory, Pre-Ahn'Qiraj caster trinket]
-
A.
isGenderSpecificCategory
Indicates that the category applies specifically to one gender rather than being gender-neutral.
-
B.
gear
Indicates that one entity functions as a gear or toothed mechanical component that transmits motion or force to another entity.
-
C.
hardwareCategory
Indicates that an item belongs to or is classified under a specific hardware category or type.
-
D.
weaponCategory
Indicates the classification or type of weapon to which an item or armament belongs.
-
E.
gearStyle
Indicates the type or manner of gear configuration or usage associated with an 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcdaa2bfc08190beccabb0f1782d0d |
completed | May 7, 2026, 6:32 p.m. |
Created at: May 3, 2026, 4:32 p.m.