Triple
T38593341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Angela Ziegler |
E932503
|
entity |
| Predicate | gameRoleMechanic |
P100032
|
FINISHED |
| Object | healer |
—
|
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: healer | Statement: [Dr. Angela Ziegler, gameRoleMechanic, healer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gameRoleMechanic Context triple: [Dr. Angela Ziegler, gameRoleMechanic, healer]
-
A.
gameplayMechanic
Indicates a relationship where one entity functions as a rule, system, or interactive feature that defines how another entity can be played or operated within a game.
-
B.
roleInGameplay
chosen
Indicates the specific function or responsibility an entity has within the context of gameplay or game mechanics.
-
C.
homeGameRole
Indicates that an entity participates in a game or match specifically in the role of the home side or host team.
-
D.
notableLevelMechanic
Indicates that an entity is recognized for its significant involvement in designing, implementing, or innovating game level mechanics.
-
E.
gameRoleInHotS
Indicates the specific role or function an entity has within the game Heroes of the Storm (HotS), such as its position or responsibility in gameplay.
- 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fce545fec881909247a3af821d21ae |
completed | May 7, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69fce12eaeec81908cf81346b2cef6e0 |
completed | May 7, 2026, 6:59 p.m. |
Created at: May 3, 2026, 4:32 p.m.