Triple
T16780083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victory |
E407833
|
entity |
| Predicate | antagonist |
P4675
|
FINISHED |
| Object | Mr. Jones |
E1233811
|
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: Mr. Jones | Statement: [Victory, antagonist, Mr. Jones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Jones Context triple: [Victory, antagonist, Mr. Jones]
-
A.
Mr. Jones
"Mr. Jones" is a hit alternative rock song by Counting Crows, known for its introspective lyrics about fame, dreams, and identity.
-
B.
Mr. Jones
Mr. Jones is a 2019 historical drama film directed by Agnieszka Holland about Welsh journalist Gareth Jones’s investigation into the Holodomor famine in Soviet Ukraine.
-
C.
Mr. Jones
chosen
Mr. Jones is the central protagonist of the novel "Victory," around whom the story’s main conflicts and themes revolve.
-
D.
Mr. Brown
Mr. Brown is the kind-hearted but often flustered father figure from the "Paddington" film series.
-
E.
Mr. Brown
Mr. Brown is one of the color-coded hijackers in the crime thriller "The Taking of Pelham One Two Three," known for his role in the subway train hostage plot.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b214cebc81909de80e74b4bac5f8 |
completed | April 18, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b287a96c8190a16d7c76d05be106 |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5:22 a.m.