Triple
T12305993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Parler |
E293353
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Parler
Parler is a social media platform known for its emphasis on minimal content moderation and popularity among right-wing and conservative users.
|
E975701
|
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: Parler | Statement: [Peter Parler, familyName, Parler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parler Context triple: [Peter Parler, familyName, Parler]
-
A.
Clubhouse
Clubhouse is a 2004 American drama film in which John Ortiz appears, centered on a troubled teen who finds an unlikely sense of belonging in a minor league baseball team’s clubhouse.
-
B.
Blackbriar
Blackbriar is a covert, off-the-books CIA black ops program featured in the Jason Bourne film series, known for its illegal assassination and surveillance activities.
-
C.
Mumble
Mumble is the tap-dancing emperor penguin protagonist of the animated film "Happy Feet."
-
D.
Agora
Agora is a 2009 historical drama film set in Roman Egypt that explores religious conflict and the life of philosopher Hypatia.
-
E.
Agora
Agora is the industry-focused market and networking hub of the Thessaloniki International Film Festival, dedicated to supporting film professionals and promoting new projects.
- 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: Parler Triple: [Peter Parler, familyName, Parler]
Generated description
Parler is a social media platform known for its emphasis on minimal content moderation and popularity among right-wing and conservative users.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Parler Target entity description: Parler is a social media platform known for its emphasis on minimal content moderation and popularity among right-wing and conservative users.
-
A.
Clubhouse
Clubhouse is a 2004 American drama film in which John Ortiz appears, centered on a troubled teen who finds an unlikely sense of belonging in a minor league baseball team’s clubhouse.
-
B.
Blackbriar
Blackbriar is a covert, off-the-books CIA black ops program featured in the Jason Bourne film series, known for its illegal assassination and surveillance activities.
-
C.
Mumble
Mumble is the tap-dancing emperor penguin protagonist of the animated film "Happy Feet."
-
D.
Agora
Agora is the industry-focused market and networking hub of the Thessaloniki International Film Festival, dedicated to supporting film professionals and promoting new projects.
-
E.
Agora
Agora is a 2009 historical drama film set in Roman Egypt that explores religious conflict and the life of philosopher Hypatia.
- 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_69d93f00695c8190b7365e4593631690 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e7f8fd08190bdef3bb761d53f97 |
completed | May 2, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_69f61f5cc5608190a67a888eb5136ada |
completed | May 2, 2026, 3:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62009766c8190985fafe9ba53ae7b |
completed | May 2, 2026, 4:02 p.m. |
Created at: April 8, 2026, 9:53 p.m.