Triple
T27811800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pym Technologies |
E702535
|
entity |
| Predicate | conflictTypeInStories |
P1397
|
FINISHED |
| Object | corporate espionage |
—
|
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: corporate espionage | Statement: [Pym Technologies, conflictTypeInStories, corporate espionage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictTypeInStories Context triple: [Pym Technologies, conflictTypeInStories, corporate espionage]
-
A.
conflictType
chosen
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
B.
conflictDescribedIn
Indicates that a particular conflict is documented, detailed, or discussed within a specified information source or description.
-
C.
storyConflict
Indicates a relationship where a story contains or centers around a central problem, opposition, or tension that drives its plot.
-
D.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
E.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
- 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6617ba4a88190bfc5c305acb4f93f |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 27, 2026, 5:43 p.m.