Triple
T3139549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan Reynolds |
E65610
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Deadpool |
E169776
|
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: Deadpool | Statement: [Ryan Reynolds, notableWork, Deadpool]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deadpool Context triple: [Ryan Reynolds, notableWork, Deadpool]
-
A.
Deadpool
chosen
Deadpool is a popular Marvel Comics antihero known for his dark humor, constant fourth-wall breaking, and ultra-violent, self-aware adventures.
-
B.
Deadpool 2
Deadpool 2 is a 2018 superhero action-comedy film based on the Marvel Comics character Deadpool, known for its irreverent humor, graphic violence, and self-aware parody of the genre.
-
C.
Logan
Logan is a 2017 superhero film in the X-Men franchise that follows an aging Wolverine on a violent, character-driven road journey in a bleak near-future.
-
D.
Logan
Logan is a neighborhood in Wyoming, Ohio, that serves as the community surrounding the Wyoming train station.
-
E.
Logan
Logan is a name commonly used as both a given name and surname in English-speaking countries.
- 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada57743e08190a1069c62e32f1bd4 |
completed | March 8, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b224e11c508190b69c16dfb5313fc2 |
completed | March 12, 2026, 2:28 a.m. |
Created at: March 8, 2026, 3:05 p.m.