Triple
T36182427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binx |
E1046751
|
entity |
| Predicate | placeOfCurse |
P194724
|
FINISHED |
| Object | Salem, Massachusetts |
—
|
NE NERFINISHED |
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: Salem, Massachusetts | Statement: [Binx, placeOfCurse, Salem, Massachusetts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placeOfCurse Context triple: [Binx, placeOfCurse, Salem, Massachusetts]
-
A.
associatedCurse
Indicates that one entity is linked to, affected by, or bears responsibility for a particular curse related to another entity.
-
B.
curseName
Indicates that one entity assigns, uses, or is associated with a specific name or label used as a curse toward another entity.
-
C.
curseTrigger
Indicates that one entity causes, activates, or is responsible for initiating a curse that affects another entity.
-
D.
curseSymbol
Indicates that one entity serves as a symbol, sign, or representation of a curse associated with another entity.
-
E.
curseCondition
Indicates a condition or state in which an entity is affected by a curse or cursed effect.
- 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_69f76e3c1b10819081fc7a807a71cf84 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
| PDg | Predicate description generation | batch_69fd82ebe1c081908455fc45b6e45178 |
completed | May 8, 2026, 6:30 a.m. |
Created at: May 3, 2026, 4:08 p.m.