Triple
T2200894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperator Furiosa |
E50484
|
entity |
| Predicate | seeks |
P860
|
FINISHED |
| Object |
Green Place
Green Place is the idyllic, fertile homeland from the film "Mad Max: Fury Road" that represents hope and refuge in a post-apocalyptic wasteland.
|
E242752
|
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: Green Place | Statement: [Imperator Furiosa, seeks, Green Place]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Green Place Context triple: [Imperator Furiosa, seeks, Green Place]
-
A.
The Lawn
The Lawn is the historic, colonnaded central quadrangle of the University of Virginia, designed by Thomas Jefferson as the heart of his Academical Village.
-
B.
Goose Hollow
Goose Hollow is a historic, centrally located neighborhood in Portland, Oregon, known for its mix of residential streets, urban amenities, and proximity to downtown.
-
C.
Green Hill Park
Green Hill Park is a large public park in Worcester, Massachusetts, known for its open green spaces, recreational facilities, and scenic views.
-
D.
Greenmeadow
Greenmeadow is a residential neighbourhood within the town of Cwmbran in South Wales.
-
E.
Hillside
Hillside is the former Concord, Massachusetts home of author Nathaniel Hawthorne, now a historic site known as The Wayside.
- 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: Green Place Triple: [Imperator Furiosa, seeks, Green Place]
Generated description
Green Place is the idyllic, fertile homeland from the film "Mad Max: Fury Road" that represents hope and refuge in a post-apocalyptic wasteland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Green Place Target entity description: Green Place is the idyllic, fertile homeland from the film "Mad Max: Fury Road" that represents hope and refuge in a post-apocalyptic wasteland.
-
A.
The Lawn
The Lawn is the historic, colonnaded central quadrangle of the University of Virginia, designed by Thomas Jefferson as the heart of his Academical Village.
-
B.
Goose Hollow
Goose Hollow is a historic, centrally located neighborhood in Portland, Oregon, known for its mix of residential streets, urban amenities, and proximity to downtown.
-
C.
Green Hill Park
Green Hill Park is a large public park in Worcester, Massachusetts, known for its open green spaces, recreational facilities, and scenic views.
-
D.
Greenmeadow
Greenmeadow is a residential neighbourhood within the town of Cwmbran in South Wales.
-
E.
Hillside
Hillside is the former Concord, Massachusetts home of author Nathaniel Hawthorne, now a historic site known as The Wayside.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa06bb4819092d7021358846e5f |
completed | March 7, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5dbd583c8190bc7355bdf94d6588 |
completed | March 9, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69ae5e6f8eb481908d75d2c648a88af4 |
completed | March 9, 2026, 5:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5edfe80481908c3304c917c9065b |
completed | March 9, 2026, 5:47 a.m. |
Created at: March 4, 2026, 7:46 p.m.