Triple
T14114805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jai Paul |
E339740
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Paul |
E3700
|
NE FINISHED |
How this triple was built (2 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: Paul | Statement: [Jai Paul, familyName, Paul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Context triple: [Jai Paul, familyName, Paul]
-
A.
Paul
Paul is a laid-back, charming sperm donor whose unexpected involvement with his biological children disrupts a lesbian couple’s family dynamic in the film "The Kids Are All Right."
-
B.
Paul
Paul is a character from the film "Nobody’s Business," contributing to the story’s exploration of personal and family relationships.
-
C.
Paul
Paul is the tormented protagonist of Erich Wolfgang Korngold’s opera "Die tote Stadt," struggling with grief and obsession over his dead wife in the decaying city of Bruges.
-
D.
Paul
chosen
Paul is a masculine given name of Latin origin, widely used in many Western and Christian-influenced cultures.
-
E.
Paul
Paul is a 2011 sci-fi comedy film about two British geeks who encounter a wisecracking alien during a road trip across the United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de600f992c81908133813f2894dcca |
completed | April 14, 2026, 3:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0b881388190a5bcdd87fd10c516 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:22 p.m.