Triple
T9400336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-1000 |
E226450
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Robert Patrick |
E201580
|
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: Robert Patrick | Statement: [T-1000, portrayedBy, Robert Patrick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Patrick Context triple: [T-1000, portrayedBy, Robert Patrick]
-
A.
Robert Patrick
chosen
Robert Patrick is an American actor best known for his roles in films like "Terminator 2: Judgment Day" and television series such as "The X-Files" and "The Unit."
-
B.
Robert Urich
Robert Urich was an American actor best known for his roles in television series such as "Vega$," "Spenser: For Hire," and "Lonesome Dove."
-
C.
Stephen Norton
Stephen Norton is a mathematician known for his contributions to the theory of finite groups and the Monster group in particular.
-
D.
Thomas Jane
Thomas Jane is an American actor best known for his roles in films such as "The Punisher," "Deep Blue Sea," and "Boogie Nights," as well as the TV series "The Expanse."
-
E.
Jeremy Grey
Jeremy Grey is a charismatic, fast-talking divorce mediator and womanizer portrayed by Vince Vaughn in the comedy film "Wedding Crashers."
- 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5156b9588190bafb6b1c3ee3c0ed |
completed | April 1, 2026, 5:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d110214f088190a972c8534b613873 |
completed | April 4, 2026, 1:20 p.m. |
Created at: March 30, 2026, 7:46 p.m.