Triple
T8433280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gamora |
E199165
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Gamora (Marvel Comics) |
E199165
|
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: Gamora (Marvel Comics) | Statement: [Gamora, basedOn, Gamora (Marvel Comics)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gamora (Marvel Comics) Context triple: [Gamora, basedOn, Gamora (Marvel Comics)]
-
A.
Gamora
chosen
Gamora is a skilled assassin and adopted daughter of Thanos who becomes a key member of the Guardians of the Galaxy in the Marvel Cinematic Universe.
-
B.
Ronan the Accuser
Ronan the Accuser is a powerful Kree zealot and primary antagonist in the Marvel Cinematic Universe, best known for his role as the villain opposing the Guardians of the Galaxy.
-
C.
Jennifer Walters
Jennifer Walters is a Marvel Comics lawyer who becomes the superhero She-Hulk after receiving a blood transfusion from her cousin Bruce Banner.
-
D.
Scarlet Witch
Scarlet Witch is a powerful Marvel Comics superhero and Avenger, known for her reality-warping chaos magic and complex moral journey.
-
E.
Jane Foster
Jane Foster is a brilliant astrophysicist and Thor’s primary human love interest in Marvel’s Thor films.
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbd1a74d948190abd76e7a6efb42ec |
completed | March 31, 2026, 1:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce399e8efc8190ad6fa8a6cf91797c |
completed | April 2, 2026, 9:40 a.m. |
Created at: March 30, 2026, 6:07 p.m.