Triple
T17908538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Tennyson |
E447762
|
entity |
| Predicate | hasDeviceForm |
P9919
|
FINISHED |
| Object | Omnitrix bearer |
—
|
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: Omnitrix bearer | Statement: [Ben Tennyson, hasDeviceForm, Omnitrix bearer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDeviceForm Context triple: [Ben Tennyson, hasDeviceForm, Omnitrix bearer]
-
A.
hasFormFactor
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
B.
hasForm
Indicates that one entity possesses, exhibits, or is characterized by a particular shape, structure, or configuration.
-
C.
usesDevice
chosen
Indicates that one entity operates, employs, or relies on a particular device to perform an action or achieve a purpose.
-
D.
usesFormCharacteristic
Indicates that one entity employs or relies on a particular formal property or structural characteristic of another entity in performing an action or fulfilling a function.
-
E.
hasFramingDevice
Indicates that one entity serves as a narrative or structural framing device that contextualizes, introduces, or encloses the main content of another entity.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9e4c9881908bfc3a83809d6b85 |
completed | April 19, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:19 a.m.