Triple
T36960114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unmaker |
E914285
|
entity |
| Predicate | hasLoreAssociation |
P99630
|
FINISHED |
| Object | ancient demonic technology |
—
|
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: ancient demonic technology | Statement: [Unmaker, hasLoreAssociation, ancient demonic technology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoreAssociation Context triple: [Unmaker, hasLoreAssociation, ancient demonic technology]
-
A.
hasLoreContext
chosen
Indicates that something is associated with or situated within a particular narrative, historical, or fictional background or storyline.
-
B.
hasLegendAssociatedWith
Indicates that something is connected to or accompanied by a traditional story, myth, or legend.
-
C.
materialInLore
Indicates that a material is referenced, described, or plays a role within a body of lore or fictional/worldbuilding context.
-
D.
hasHeirloom
Indicates that one entity possesses or is associated with an heirloom originating from another entity.
-
E.
hasCharacterAssociated
Indicates that one entity is linked to or connected with a particular character (such as a person, figure, or persona) in some relevant way.
- 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_69f76e8c498c8190b2842db80aea8b3b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff779e3f0c8190a861f1e4000fd9d9 |
completed | May 9, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69ff77202638819086e4b9f9c0bc7b31 |
completed | May 9, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:13 p.m.