Triple
T34958335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annika Hansen |
E1008177
|
entity |
| Predicate | hasImplants |
P54723
|
FINISHED |
| Object | Borg technology |
—
|
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: Borg technology | Statement: [Annika Hansen, hasImplants, Borg technology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImplants Context triple: [Annika Hansen, hasImplants, Borg technology]
-
A.
hasProsthesis
chosen
Indicates that an entity possesses or is equipped with an artificial substitute for a missing or impaired body part.
-
B.
hasAreoles
Indicates that one entity possesses or exhibits areoles as a characteristic or feature.
-
C.
hasTrueOrgans
Indicates that an entity possesses fully developed, functional organs rather than primitive or rudimentary structures.
-
D.
hasLie
Indicates that an entity is associated with or responsible for a specific lie or false statement.
-
E.
hasTrueTissues
Indicates that an organism possesses differentiated, organized tissues composed of multiple cell types performing specific functions.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4 p.m.