Triple
T18009479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T2 |
E430838
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | T-800 |
—
|
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: T-800 | Statement: [T2, character, T-800]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T-800 Context triple: [T2, character, T-800]
-
A.
T-800
chosen
The T-800 is a model of cybernetic assassin and soldier from the Terminator franchise, most famously portrayed by Arnold Schwarzenegger as a time-traveling killer robot with a human appearance.
-
B.
T-1000
The T-1000 is a shape-shifting, liquid-metal assassin android and primary antagonist in the film "Terminator 2: Judgment Day."
-
C.
T1000 train
The T1000 train is an earlier generation of electric multiple unit rolling stock used on the Oslo Metro system in Norway.
-
D.
Nexus-6 replicant
A Nexus-6 replicant is a highly advanced, bioengineered android model from the Blade Runner universe, designed to closely mimic humans in appearance and behavior while possessing superior physical capabilities.
-
E.
Kyle Reese
Kyle Reese is a time-traveling resistance fighter from the Terminator franchise, best known as John Connor’s father and protector of Sarah Connor against Skynet’s machines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b51e13788190bebbbdd7340e0982 |
completed | April 19, 2026, 10:57 a.m. |
Created at: April 10, 2026, 10:24 a.m.