Triple
T9937114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. & Mrs. Smith (2005 film) |
E193985
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Jane Smith |
E193997
|
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: Jane Smith | Statement: [Mr. & Mrs. Smith (2005 film), mainCharacter, Jane Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jane Smith Context triple: [Mr. & Mrs. Smith (2005 film), mainCharacter, Jane Smith]
-
A.
Jane Smith
chosen
Jane Smith is the fictional covert assassin and wife of John Smith played by Angelina Jolie in the action film "Mr. & Mrs. Smith."
-
B.
Anna Smith
Anna Smith is the wife of Mr. Alonzo Smith.
-
C.
Anna Smith
Anna Smith is a member of the fictional Smith family featured in the classic 1944 musical film "Meet Me in St. Louis."
-
D.
Sarah Smith
Sarah Smith is known as a daughter of early Latter-day Saint leader Hyrum Smith.
-
E.
Jean Smith
Jean Smith is known as the spouse of filmmaker Robert Stevenson.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e4e19881909879b394090d6629 |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d228e7247c81908dbba76199f2e93f |
completed | April 5, 2026, 9:18 a.m. |
Created at: March 30, 2026, 8:44 p.m.