Triple
T38590026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neltharion's Tear |
E932431
|
entity |
| Predicate | isOnUseEffect |
P191243
|
FINISHED |
| Object | False |
—
|
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: False | Statement: [Neltharion's Tear, isOnUseEffect, False]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOnUseEffect Context triple: [Neltharion's Tear, isOnUseEffect, False]
-
A.
usesEffect
Indicates that one entity employs or applies a particular effect to influence or modify another entity or outcome.
-
B.
usesEffectType
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
-
C.
runtimeEffect
Indicates that one entity has a direct impact on the performance or behavior of another during execution time.
-
D.
hasCommonSideEffect
Indicates that two or more treatments, drugs, or interventions share at least one side effect in common.
-
E.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
- 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.