Triple
T7561530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bryan Mills |
E178803
|
entity |
| Predicate | protects |
P1040
|
FINISHED |
| Object | Lenore Mills |
E673179
|
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: Lenore Mills | Statement: [Bryan Mills, protects, Lenore Mills]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lenore Mills Context triple: [Bryan Mills, protects, Lenore Mills]
-
A.
Lenore Mills
chosen
Lenore Mills is the protagonist of the film "Taken," around whom the story’s kidnapping and rescue plot revolves.
-
B.
Barbara Mallery
Barbara Mallery was the first wife of American television and radio personality Dick Clark, whom he married early in his career.
-
C.
Diane Millstead
Diane Millstead is an Australian academic and writer best known as the former wife of comedian and satirist Barry Humphries.
-
D.
Phyllis Lindstrom
Phyllis Lindstrom is a snobbish, self-absorbed yet comically endearing neighbor and friend in the classic American sitcom "The Mary Tyler Moore Show."
-
E.
Lorraine Miller
Lorraine Miller was an American actress and dancer active in Hollywood films during the 1940s and 1950s.
- 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_69c69f2f80288190b95cceb4da92ab2b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8f847c48190a1081aa9de7ff945 |
completed | March 27, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8683978b48190971b4c38fd83d3cc |
completed | March 28, 2026, 11:46 p.m. |
Created at: March 27, 2026, 3:50 p.m.