Triple
T8477312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polus |
E200427
|
entity |
| Predicate | nameInGreek |
P3659
|
FINISHED |
| Object |
Πῶλος
Πῶλος (Polus) is an ancient Greek rhetorician and character in Plato’s dialogue "Gorgias," known for his discussions on rhetoric and justice.
|
E735596
|
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: Πῶλος | Statement: [Polus, nameInGreek, Πῶλος]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Πῶλος Context triple: [Polus, nameInGreek, Πῶλος]
-
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 family name most notably borne by Wolfgang Paul, the German physicist and Nobel laureate in Physics.
-
C.
Paul
Paul is a notable town on the Cape Verdean island of Santo Antão, known for its lush valleys and traditional rural life.
-
D.
Paul
Paul is the middle-aged American widower portrayed by Marlon Brando in the controversial 1972 film "Last Tango in Paris."
-
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. 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: Πῶλος Triple: [Polus, nameInGreek, Πῶλος]
Generated description
Πῶλος (Polus) is an ancient Greek rhetorician and character in Plato’s dialogue "Gorgias," known for his discussions on rhetoric and justice.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Πῶλος Target entity description: Πῶλος (Polus) is an ancient Greek rhetorician and character in Plato’s dialogue "Gorgias," known for his discussions on rhetoric and justice.
-
A.
Paul
Paul is a family name most notably borne by Wolfgang Paul, the German physicist and Nobel laureate in Physics.
-
B.
Paul
Paul is the middle-aged American widower portrayed by Marlon Brando in the controversial 1972 film "Last Tango in Paris."
-
C.
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."
-
D.
Paul
Paul is a village and civil parish in Cornwall, England, known for its historic church and coastal setting near Penzance.
-
E.
Paul
Paul is a notable town on the Cape Verdean island of Santo Antão, known for its lush valleys and traditional rural life.
- 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe51ffab881908448aff899511f2c |
completed | March 31, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce3a196ad48190b3887a2a0c43f87f |
completed | April 2, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_69ce3b1f6f7c8190927b5e2684ae207b |
completed | April 2, 2026, 9:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce3b9d38e081909be10cb209b15427 |
completed | April 2, 2026, 9:49 a.m. |
Created at: March 30, 2026, 6:12 p.m.