Triple
T17630694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | India Stoker |
E429967
|
entity |
| Predicate | hasAffinityFor |
P87255
|
FINISHED |
| Object | violence |
—
|
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: violence | Statement: [India Stoker, hasAffinityFor, violence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAffinityFor Context triple: [India Stoker, hasAffinityFor, violence]
-
A.
hasUncertainAffinityWith
Indicates a relationship where the strength, nature, or existence of affinity between two entities is unclear, variable, or not confidently established.
-
B.
possibleAffinity
chosen
Indicates a potential or likely positive relationship, attraction, or compatibility between two entities, without asserting that it is confirmed or realized.
-
C.
hasAffiliationModel
Indicates that one entity uses, follows, or is governed by a particular affiliation model in its relationships or organizational structure.
-
D.
hasStrongTiesTo
Indicates a close, influential, and enduring relationship or connection exists between the referenced entities.
-
E.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dc01b1c819099e3329cfb8cb77f |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:52 a.m.