Triple
T19552265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arena |
E489223
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Kylan Amos
Kylan Amos is a professional rugby league player who competes for the New Zealand Warriors in the National Rugby League (NRL).
|
E1381209
|
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: Kylan Amos | Statement: [Arena, hasMember, Kylan Amos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kylan Amos Context triple: [Arena, hasMember, Kylan Amos]
-
A.
Jaden Oshenye
Jaden Oshenye is a notable participant featured on the reality TV show "Red, White and Blue."
-
B.
Jojo Townsell
Jojo Townsell is a former American football wide receiver best known for his play in the USFL and later with the New York Jets in the NFL.
-
C.
Kallum Watkins
Kallum Watkins is an English professional rugby league footballer best known for his successful career as a centre for Leeds Rhinos and the England national team.
-
D.
Mathew Ector
Mathew Ector was a 19th-century American Confederate general and Texas jurist for whom Ector County, Texas, is named.
-
E.
Kedar Williams-Stirling
Kedar Williams-Stirling is a British actor best known for his role as Jackson Marchetti in the Netflix comedy-drama series "Sex Education."
- 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: Kylan Amos Triple: [Arena, hasMember, Kylan Amos]
Generated description
Kylan Amos is a professional rugby league player who competes for the New Zealand Warriors in the National Rugby League (NRL).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kylan Amos Target entity description: Kylan Amos is a professional rugby league player who competes for the New Zealand Warriors in the National Rugby League (NRL).
-
A.
Jaden Oshenye
Jaden Oshenye is a notable participant featured on the reality TV show "Red, White and Blue."
-
B.
Jojo Townsell
Jojo Townsell is a former American football wide receiver best known for his play in the USFL and later with the New York Jets in the NFL.
-
C.
Kallum Watkins
Kallum Watkins is an English professional rugby league footballer best known for his successful career as a centre for Leeds Rhinos and the England national team.
-
D.
Mathew Ector
Mathew Ector was a 19th-century American Confederate general and Texas jurist for whom Ector County, Texas, is named.
-
E.
Kedar Williams-Stirling
Kedar Williams-Stirling is a British actor best known for his role as Jackson Marchetti in the Netflix comedy-drama series "Sex Education."
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d30a1d8819084d1bc60a5e49cae |
completed | April 20, 2026, 2:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a074e8e25188190901a4883c5ad7f5e |
completed | May 15, 2026, 4:49 p.m. |
| NEDg | Description generation | batch_6a074ef599a88190a1edd95887a0c092 |
completed | May 15, 2026, 4:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a074fa5d4ec81908900ebf532408239 |
completed | May 15, 2026, 4:53 p.m. |
Created at: April 10, 2026, 1:41 p.m.