Triple
T12307707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hive (MCU) |
E293395
|
entity |
| Predicate | controls |
P760
|
FINISHED |
| Object |
Giyera
Giyera is a telekinetic Inhuman and former HYDRA operative in the Marvel Cinematic Universe who serves as a loyal enforcer to the ancient Inhuman entity Hive.
|
E974288
|
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: Giyera | Statement: [Hive (MCU), controls, Giyera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Giyera Context triple: [Hive (MCU), controls, Giyera]
-
A.
Gizo
Gizo is a small island town in the Solomon Islands known as an administrative and commercial hub in the western part of the country and a popular base for diving and marine tourism.
-
B.
Girga
Girga is an ancient town in Upper Egypt, historically significant as a regional center along the Nile.
-
C.
Gardo
Gardo is one of the three impoverished boys who uncover a dangerous secret while scavenging through a landfill in Andy Mulligan’s novel "Trash."
-
D.
Datooga
Datooga is a Southern Nilotic language spoken primarily by the Datooga people of north-central Tanzania.
-
E.
Goria
Goria is an Italian surname most notably associated with Giovanni Goria, a former Prime Minister of Italy.
- 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: Giyera Triple: [Hive (MCU), controls, Giyera]
Generated description
Giyera is a telekinetic Inhuman and former HYDRA operative in the Marvel Cinematic Universe who serves as a loyal enforcer to the ancient Inhuman entity Hive.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Giyera Target entity description: Giyera is a telekinetic Inhuman and former HYDRA operative in the Marvel Cinematic Universe who serves as a loyal enforcer to the ancient Inhuman entity Hive.
-
A.
Gizo
Gizo is a small island town in the Solomon Islands known as an administrative and commercial hub in the western part of the country and a popular base for diving and marine tourism.
-
B.
Girga
Girga is an ancient town in Upper Egypt, historically significant as a regional center along the Nile.
-
C.
Gardo
Gardo is one of the three impoverished boys who uncover a dangerous secret while scavenging through a landfill in Andy Mulligan’s novel "Trash."
-
D.
Datooga
Datooga is a Southern Nilotic language spoken primarily by the Datooga people of north-central Tanzania.
-
E.
Goria
Goria is an Italian surname most notably associated with Giovanni Goria, a former Prime Minister of Italy.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f01ace8819087f245b9216f4dc8 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e8243d48190baf25b2927de6c62 |
completed | May 2, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_69f61f5d746c8190b5b0edfc4832bc6c |
completed | May 2, 2026, 3:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6203ef5008190af9103460b096cff |
completed | May 2, 2026, 4:03 p.m. |
Created at: April 8, 2026, 9:53 p.m.