Triple
T30598359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Augments |
E778843
|
entity |
| Predicate | mainGuestCharacter |
P169600
|
FINISHED |
| Object | Dr. Arik Soong |
—
|
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: Dr. Arik Soong | Statement: [The Augments, mainGuestCharacter, Dr. Arik Soong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainGuestCharacter Context triple: [The Augments, mainGuestCharacter, Dr. Arik Soong]
-
A.
mainCharacterField
Indicates that one entity is designated as the primary or central character associated with another entity, such as a work or narrative.
-
B.
mainAlienCharacter
Indicates that the referenced entity serves as the primary alien character in a narrative or work.
-
C.
mainMortalCharacter
Indicates that the referenced entity serves as the primary mortal (non-immortal) character in the context of a story or narrative.
-
D.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
E.
exampleCharacter
Indicates that one entity is an illustrative or sample character associated with another entity, typically used for demonstration or example purposes.
- 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_69f224a1570c8190a85d3ac330479a79 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68980c15881908953e50e05fc87e4 |
completed | May 2, 2026, 11:32 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f0353c88190a05b2db449abe0f4 |
completed | May 2, 2026, 10:47 p.m. |
Created at: April 29, 2026, 8:24 p.m.