Triple
T3989117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron Praxis |
E86943
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object |
Daxter
Daxter is a wisecracking ottsel and the comedic sidekick protagonist from the Jak and Daxter video game series.
|
E403915
|
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: Daxter | Statement: [Baron Praxis, enemyOf, Daxter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daxter Context triple: [Baron Praxis, enemyOf, Daxter]
-
A.
Banzi
Banzi is a town in the Basilicata region of southern Italy, known as the modern site near the ancient Lucanian city of Bantia.
-
B.
Sora
Sora is a historic town and comune in the Lazio region of central Italy, situated along the Liri River and known for its medieval architecture and scenic surroundings.
-
C.
Dextre
Dextre is a two-armed robotic handyman on the International Space Station designed to perform delicate maintenance tasks and reduce the need for spacewalks.
-
D.
Ratchet
Ratchet is an Autobot medic from the Transformers franchise, known for his technical expertise and role in repairing and supporting his fellow Transformers.
-
E.
Baiju
Baiju was a 13th-century Mongol general who led Mongol forces in their campaigns into Eastern Europe.
- 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: Daxter Triple: [Baron Praxis, enemyOf, Daxter]
Generated description
Daxter is a wisecracking ottsel and the comedic sidekick protagonist from the Jak and Daxter video game series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daxter Target entity description: Daxter is a wisecracking ottsel and the comedic sidekick protagonist from the Jak and Daxter video game series.
-
A.
Banzi
Banzi is a town in the Basilicata region of southern Italy, known as the modern site near the ancient Lucanian city of Bantia.
-
B.
Sora
Sora is a historic town and comune in the Lazio region of central Italy, situated along the Liri River and known for its medieval architecture and scenic surroundings.
-
C.
Dextre
Dextre is a two-armed robotic handyman on the International Space Station designed to perform delicate maintenance tasks and reduce the need for spacewalks.
-
D.
Ratchet
Ratchet is an Autobot medic from the Transformers franchise, known for his technical expertise and role in repairing and supporting his fellow Transformers.
-
E.
Baiju
Baiju was a 13th-century Mongol general who led Mongol forces in their campaigns into Eastern Europe.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa007344819099515fda367f7016 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5403235408190b47b8d4f4e21d094 |
completed | March 14, 2026, 11:02 a.m. |
| NEDg | Description generation | batch_69b540c5ab7881908b7ebb0af2f9da46 |
completed | March 14, 2026, 11:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5415e002881908343ae30b2f8a16c |
completed | March 14, 2026, 11:07 a.m. |
Created at: March 9, 2026, 3:33 p.m.