Triple
T1788498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avengers: Infinity War |
E39441
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Gamora
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.
|
E199165
|
NE FINISHED |
How this triple was built (4 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 | Statement: [Avengers: Infinity War, featuresCharacter, Gamora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gamora Context triple: [Avengers: Infinity War, featuresCharacter, Gamora]
-
A.
Jane Foster
Jane Foster is a brilliant astrophysicist and Thor’s primary human love interest in Marvel’s Thor films.
-
B.
Miss Quill
Miss Quill is a sharp-tongued, battle-hardened alien freedom fighter and teacher from the Doctor Who spin-off series "Class."
-
C.
Loki
Loki is a trickster god in Norse mythology known for his shape-shifting, cunning, and role in both aiding and undermining the other gods.
-
D.
Mara Wilson
Mara Wilson is an American former child actress and writer best known for her roles in films like "Matilda," "Mrs. Doubtfire," and "Miracle on 34th Street."
-
E.
Sif
Sif is a goddess in Norse mythology best known as the golden-haired wife of Thor and a deity associated with earth, fertility, and grain.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gamora Triple: [Avengers: Infinity War, featuresCharacter, Gamora]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gamora Target entity description: 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.
-
A.
Jane Foster
Jane Foster is a brilliant astrophysicist and Thor’s primary human love interest in Marvel’s Thor films.
-
B.
Miss Quill
Miss Quill is a sharp-tongued, battle-hardened alien freedom fighter and teacher from the Doctor Who spin-off series "Class."
-
C.
Loki
Loki is a trickster god in Norse mythology known for his shape-shifting, cunning, and role in both aiding and undermining the other gods.
-
D.
Mara Wilson
Mara Wilson is an American former child actress and writer best known for her roles in films like "Matilda," "Mrs. Doubtfire," and "Miracle on 34th Street."
-
E.
Sif
Sif is a goddess in Norse mythology best known as the golden-haired wife of Thor and a deity associated with earth, fertility, and grain.
- F. None of above. chosen
Provenance (5 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa650fd3448190a6a2c979db982cae |
completed | March 6, 2026, 5:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9a8a69c8190885bf06a06d3869f |
completed | March 8, 2026, 4:54 p.m. |
| NEDg | Description generation | batch_69adaab488ec81909a340aab4916b90f |
completed | March 8, 2026, 4:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adaf3cd23081909dd27c5de8e3f6d2 |
completed | March 8, 2026, 5:17 p.m. |
Created at: March 4, 2026, 7:32 p.m.