Triple
T31240791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wild Mountain Thyme |
E796553
|
entity |
| Predicate | characterPlayedByChristopherWalken |
P196787
|
FINISHED |
| Object | Tony Reilly |
—
|
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: Tony Reilly | Statement: [Wild Mountain Thyme, characterPlayedByChristopherWalken, Tony Reilly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedByChristopherWalken Context triple: [Wild Mountain Thyme, characterPlayedByChristopherWalken, Tony Reilly]
-
A.
characterPlayedBy_Charles Bronson
Indicates that a given character is portrayed or acted by Charles Bronson.
-
B.
characterPlayedByGeneHackman
Indicates that a given character is portrayed or acted by Gene Hackman.
-
C.
characterPlayedByRobertPatrick
Indicates that a given character is portrayed or acted by Robert Patrick.
-
D.
characterPlayedByRichardHarris
Indicates that the subject is a character that was portrayed by the actor Richard Harris.
-
E.
characterPlayedByMarlonBrando
Indicates that the character in question is portrayed or acted by Marlon Brando.
- F. None of above. chosen
Provenance (4 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_69f224db69ac81909a370adad6a7ac7c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
| PDg | Predicate description generation | batch_69fe68a385f48190b942700e3eddc9b6 |
completed | May 8, 2026, 10:50 p.m. |
Created at: April 29, 2026, 9:11 p.m.