Triple
T30070955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 100 Girls |
E764180
|
entity |
| Predicate | characterPlayedBy Jonathan Tucker |
P195274
|
FINISHED |
| Object | Matthew |
—
|
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: Matthew | Statement: [100 Girls, characterPlayedBy Jonathan Tucker, Matthew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedBy Jonathan Tucker Context triple: [100 Girls, characterPlayedBy Jonathan Tucker, Matthew]
-
A.
characterPlayedBy Kenneth Connor
Indicates that a character is portrayed or acted by Kenneth Connor.
-
B.
characterPlayedByEdwardMulhare
Indicates that the subject is a character that was portrayed or played by Edward Mulhare.
-
C.
characterVoicedBy Seann William Scott
Indicates that a character is voiced by Seann William Scott.
-
D.
characterPlayedBy_Freddy Rodríguez
Indicates that a given character is portrayed or played by the actor Freddy Rodríguez.
-
E.
characterVoicedBy Denis Leary
Indicates that the character is voiced by Denis Leary.
- 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_69f2247221388190a13a22c47094a0ef |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
| PDg | Predicate description generation | batch_69fdb4544b548190b8971f8055d48caa |
completed | May 8, 2026, 10 a.m. |
Created at: April 29, 2026, 7 p.m.