Triple
T31240790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wild Mountain Thyme |
E796553
|
entity |
| Predicate | characterPlayedByJonHamm |
P196749
|
FINISHED |
| Object | Adam Kelly |
—
|
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: Adam Kelly | Statement: [Wild Mountain Thyme, characterPlayedByJonHamm, Adam Kelly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedByJonHamm Context triple: [Wild Mountain Thyme, characterPlayedByJonHamm, Adam Kelly]
-
A.
characterPlayedByJamieDornan
Indicates that the subject is a character portrayed by the actor Jamie Dornan.
-
B.
characterPlayedByRichardHarris
Indicates that the subject is a character that was portrayed by the actor Richard Harris.
-
C.
characterPlayedBy Jonathan Tucker
Indicates that the specified character is portrayed or acted by Jonathan Tucker.
-
D.
characterPlayedBySamuelLJackson
Indicates that the subject is a character portrayed by the actor Samuel L. Jackson.
-
E.
characterPlayedByRobertPatrick
Indicates that a given character is portrayed or acted by Robert Patrick.
- 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_69fe6739d4dc8190ae7505c089bbac29 |
completed | May 8, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69fe6541dffc81909c66a61ba69f38fc |
completed | May 8, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69fe673905408190a2ae68c2c9563403 |
completed | May 8, 2026, 10:44 p.m. |
Created at: April 29, 2026, 9:11 p.m.