Triple
T21117069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CBGB (film) |
E520326
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object |
XLrator Media
XLrator Media is an independent film distribution company known for releasing genre and specialty films across various platforms.
|
E1468108
|
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: XLrator Media | Statement: [CBGB (film), distributor, XLrator Media]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XLrator Media Context triple: [CBGB (film), distributor, XLrator Media]
-
A.
LXS
LXS is the IATA airport code for the main airport serving the Greek island of Lemnos in the northern Aegean Sea.
-
B.
XRL
XRL is a high-speed rail line connecting Guangzhou, Shenzhen, and Hong Kong, forming a key part of China’s national high-speed railway network.
-
C.
Lava Media
Lava Media is a film production company known for its involvement in the acclaimed adaptation of Aravind Adiga’s novel "The White Tiger."
-
D.
Elx
Elx, also known as Elche, is a historic city in Spain’s Valencian Community renowned for its vast palm grove and rich cultural heritage.
-
E.
Ebixa
Ebixa is a brand-name medication containing memantine, used primarily to treat moderate to severe Alzheimer's disease.
- 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: XLrator Media Triple: [CBGB (film), distributor, XLrator Media]
Generated description
XLrator Media is an independent film distribution company known for releasing genre and specialty films across various platforms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: XLrator Media Target entity description: XLrator Media is an independent film distribution company known for releasing genre and specialty films across various platforms.
-
A.
LXS
LXS is the IATA airport code for the main airport serving the Greek island of Lemnos in the northern Aegean Sea.
-
B.
XRL
XRL is a high-speed rail line connecting Guangzhou, Shenzhen, and Hong Kong, forming a key part of China’s national high-speed railway network.
-
C.
Lava Media
Lava Media is a film production company known for its involvement in the acclaimed adaptation of Aravind Adiga’s novel "The White Tiger."
-
D.
Elx
Elx, also known as Elche, is a historic city in Spain’s Valencian Community renowned for its vast palm grove and rich cultural heritage.
-
E.
Ebixa
Ebixa is a brand-name medication containing memantine, used primarily to treat moderate to severe Alzheimer's disease.
- 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72106a3b48190a0efa51a74ae21f0 |
completed | April 21, 2026, 7:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0965e5b04c8190addaa49cb9f6ad06 |
completed | May 17, 2026, 6:53 a.m. |
| NEDg | Description generation | batch_6a0969cd36b081909e24ab92c0b2ab0a |
completed | May 17, 2026, 7:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a096b373290819082f45e68772a81e4 |
completed | May 17, 2026, 7:16 a.m. |
Created at: April 16, 2026, 2:55 p.m.