Triple
T22768580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Color of Night |
E563191
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Lance Henriksen |
—
|
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: Lance Henriksen | Statement: [Color of Night, starring, Lance Henriksen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lance Henriksen Context triple: [Color of Night, starring, Lance Henriksen]
-
A.
Lance Henriksen
chosen
Lance Henriksen is an American character actor best known for his intense performances in science fiction and horror films such as the Alien franchise and the TV series Millennium.
-
B.
Michael Kane
Michael Kane is a creator known for developing the character Stefen Djordjevic.
-
C.
Michael Kane
Michael Kane is a screenwriter best known for writing the 1983 American sports drama film "All the Right Moves."
-
D.
Michael Ironside
Michael Ironside is a Canadian actor known for his intense, often villainous roles in science fiction and action films such as "Total Recall," "Starship Troopers," and "Top Gun."
-
E.
Miguel Ferrer
Miguel Ferrer was an American character actor known for his intense, often villainous roles in film and television, including notable performances in projects like "RoboCop," "Twin Peaks," and "NCIS: Los Angeles."
- 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b59c9cc8190a6edd68f3209a672 |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 3:27 p.m.