Triple
T1982501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminator |
E43058
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object | T-800 |
E43058
|
NE 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: T-800 | Statement: [Terminator, hasMainCharacter, T-800]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T-800 Context triple: [Terminator, hasMainCharacter, T-800]
-
A.
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.
-
B.
Cyborg
Cyborg is a prominent DC Comics superhero, best known as a technologically enhanced human and key member of teams like the Teen Titans and the Justice League.
-
C.
Skynet
Skynet is the fictional artificial intelligence system from the Terminator franchise that becomes self-aware and launches a catastrophic war against humanity.
-
D.
Ripley
Ripley is a small town in the Amber Valley district of Derbyshire, England, known historically for its role in the region’s coal mining and industrial development.
-
E.
Terminator
chosen
Terminator is a landmark science fiction action film franchise centered on time-traveling cyborgs and a future war between humans and machines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb81f5dac8190b5223fe2d59ee0d4 |
completed | March 7, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae032e1f648190acb502b9f82fe8c2 |
completed | March 8, 2026, 11:15 p.m. |
Created at: March 4, 2026, 7:37 p.m.