Triple
T14413683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jules Mann-Stewart |
E357393
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
K-11
K-11 is an independent drama film set in a Los Angeles jail unit for LGBTQ+ inmates, directed by Jules Mann-Stewart and known for its gritty, character-driven story.
|
E1097689
|
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: K-11 | Statement: [Jules Mann-Stewart, notableWork, K-11]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K-11 Context triple: [Jules Mann-Stewart, notableWork, K-11]
-
A.
K-10
K-10 is a state highway in Kansas that serves as a major east–west commuter and connector route in the Kansas City metropolitan area.
-
B.
K-14
K-14 is a state highway in Kansas that runs through Ellsworth County, serving as part of the regional transportation network in central Kansas.
-
C.
K-15
K-15 is a state highway in Kansas that runs north–south, connecting several rural communities and regional routes across the state.
-
D.
K1
K1, also known as Masherbrum, is a prominent 7,821-meter peak in the Karakoram range of Pakistan and one of the world’s highest mountains.
-
E.
K1
K1 is the first highly accurate marine chronometer built by Larcum Kendall in the 18th century, famous for its role in improving longitude determination at sea.
- 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: K-11 Triple: [Jules Mann-Stewart, notableWork, K-11]
Generated description
K-11 is an independent drama film set in a Los Angeles jail unit for LGBTQ+ inmates, directed by Jules Mann-Stewart and known for its gritty, character-driven story.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: K-11 Target entity description: K-11 is an independent drama film set in a Los Angeles jail unit for LGBTQ+ inmates, directed by Jules Mann-Stewart and known for its gritty, character-driven story.
-
A.
K-10
K-10 is a state highway in Kansas that serves as a major east–west commuter and connector route in the Kansas City metropolitan area.
-
B.
K-14
K-14 is a state highway in Kansas that runs through Ellsworth County, serving as part of the regional transportation network in central Kansas.
-
C.
K-15
K-15 is a state highway in Kansas that runs north–south, connecting several rural communities and regional routes across the state.
-
D.
K1
K1, also known as Masherbrum, is a prominent 7,821-meter peak in the Karakoram range of Pakistan and one of the world’s highest mountains.
-
E.
K1
K1 is the first highly accurate marine chronometer built by Larcum Kendall in the 18th century, famous for its role in improving longitude determination at sea.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cb3c708190822f5506ebf7ee9d |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd552858208190ba1550e7c1176a2a |
completed | May 8, 2026, 3:14 a.m. |
| NEDg | Description generation | batch_69fd5671e4688190ab1b7a7ed6c0cfb8 |
completed | May 8, 2026, 3:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd57710f648190a1344ac1363acce1 |
completed | May 8, 2026, 3:24 a.m. |
Created at: April 10, 2026, 1:17 a.m.