Triple
T3240157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downhill |
E67946
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Pamela Martin |
E458105
|
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: Pamela Martin | Statement: [Downhill, editedBy, Pamela Martin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pamela Martin Context triple: [Downhill, editedBy, Pamela Martin]
-
A.
Pamela Martin
chosen
Pamela Martin is an American film editor known for her work on acclaimed movies such as "The Fighter" and "Little Miss Sunshine."
-
B.
Pamela Pettler
Pamela Pettler is an American screenwriter best known for her work on darkly comedic animated films such as "Corpse Bride" and "Monster House."
-
C.
Pamela Brown
Pamela Brown was a British stage and film actress known for her intense character roles in mid-20th-century cinema and theatre.
-
D.
Pamela Jones
Pamela Jones is the fictional, somewhat overbearing but well-meaning mother of Bridget Jones in the "Bridget Jones" novels and film adaptations.
-
E.
Pam Ferris
Pam Ferris is a British actress known for her character roles in film and television, including memorable performances in "Matilda," "Call the Midwife," and "Harry Potter and the Prisoner of Azkaban."
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef6430081909084589f6eea5c7e |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07d33a65481908c7ab4473bed1320 |
completed | March 22, 2026, 11:37 p.m. |
Created at: March 8, 2026, 3:08 p.m.