Triple
T5778542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mason Lee |
E127503
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Limbo
Limbo is a film featuring actor Mason Lee in a prominent role.
|
E546159
|
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: Limbo | Statement: [Mason Lee, notableWork, Limbo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limbo Context triple: [Mason Lee, notableWork, Limbo]
-
A.
Limbo
Limbo is a critically acclaimed 2020 hip-hop album by American rapper Aminé that blends introspective lyricism with vibrant, melodic production.
-
B.
Limbo
Limbo is a critically acclaimed 2010 indie puzzle-platform video game known for its monochromatic art style, eerie atmosphere, and physics-based environmental puzzles.
-
C.
Limbo
Limbo is the first circle of Hell in Dante Alighieri’s Divine Comedy, depicted as the abode of virtuous pagans and unbaptized souls who live without torment but forever separated from God.
-
D.
Descent into Limbo
Descent into Limbo is a large-scale installation artwork by Anish Kapoor featuring a seemingly bottomless black void that challenges viewers’ perception of depth and space.
-
E.
The Pit
The Pit is a famed college basketball arena in Albuquerque, New Mexico, renowned for its intense atmosphere and distinctive sunken design.
- 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: Limbo Triple: [Mason Lee, notableWork, Limbo]
Generated description
Limbo is a film featuring actor Mason Lee in a prominent role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Limbo Target entity description: Limbo is a film featuring actor Mason Lee in a prominent role.
-
A.
Limbo
Limbo is a critically acclaimed 2010 indie puzzle-platform video game known for its monochromatic art style, eerie atmosphere, and physics-based environmental puzzles.
-
B.
Limbo
Limbo is a critically acclaimed 2020 hip-hop album by American rapper Aminé that blends introspective lyricism with vibrant, melodic production.
-
C.
Limbo
Limbo is the first circle of Hell in Dante Alighieri’s Divine Comedy, depicted as the abode of virtuous pagans and unbaptized souls who live without torment but forever separated from God.
-
D.
Descent into Limbo
Descent into Limbo is a large-scale installation artwork by Anish Kapoor featuring a seemingly bottomless black void that challenges viewers’ perception of depth and space.
-
E.
The Pit
The Pit is a famed college basketball arena in Albuquerque, New Mexico, renowned for its intense atmosphere and distinctive sunken design.
- 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_69c008361fa88190aefa4dc41b051e7f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029e107348190a03086f1cbfae0d3 |
completed | March 22, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e735f408190b188b94131f1e51b |
completed | March 22, 2026, 11:42 p.m. |
| NEDg | Description generation | batch_69c08dc00df48190ad2cf716ad6eeb87 |
completed | March 23, 2026, 12:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c08e3b05a881909892ce776309920d |
completed | March 23, 2026, 12:50 a.m. |
Created at: March 22, 2026, 3:50 p.m.