Triple
T12223152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Carter |
E291270
|
entity |
| Predicate | appearsInTVSeries |
P795
|
FINISHED |
| Object | What If...? |
E508816
|
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: What If...? | Statement: [Margaret Carter, appearsInTVSeries, What If...?]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: What If...? Context triple: [Margaret Carter, appearsInTVSeries, What If...?]
-
A.
What If...? (TV series)
chosen
What If...? is a Marvel Studios animated anthology series that explores alternate timelines and reimagined scenarios within the Marvel Cinematic Universe.
-
B.
What If?
What If? is Randall Munroe’s popular science blog (and later book) where he answers bizarre hypothetical questions using rigorous scientific reasoning and humor.
-
C.
What If?
"What If?" is a song by the American rock band Creed, known for its heavy guitar riffs and introspective lyrics.
-
D.
What If
What If is a romantic comedy film best known for its witty exploration of friendship and love, starring Daniel Radcliffe and Mackenzie Davis.
-
E.
What If
"What If" is a song by the South Korean hip hop duo X&Y.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ca11f788190bad2efb6c83ffccb |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aa6d3d481909852a6f2f90d7a41 |
completed | May 2, 2026, 2:31 p.m. |
Created at: April 8, 2026, 9:51 p.m.