Triple
T4629832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto Marlboros |
E101385
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Marlies
Marlies is the common nickname for the Toronto Marlboros, a historic Canadian junior ice hockey team based in Toronto.
|
E457613
|
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: Marlies | Statement: [Toronto Marlboros, alsoKnownAs, Marlies]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marlies Context triple: [Toronto Marlboros, alsoKnownAs, Marlies]
-
A.
Anneliese Bahr
Anneliese Bahr was the wife of German industrialist Alfried Krupp von Bohlen und Halbach, heir to the Krupp steel and armaments empire.
-
B.
Josephine Bruin
Josephine Bruin is one of the costumed bear mascots representing the University of California, Los Angeles at athletic events and campus activities.
-
C.
Dolly Haas
Dolly Haas was a German-born actress and singer known for her work in European cinema and later on Broadway and in American films.
-
D.
Jolanda
Jolanda is a feminine given name, commonly considered a variant of Yolanda, used in various European countries.
-
E.
Kamilla
Kamilla is a Brazilian professional basketball player known for her standout collegiate career at Syracuse and South Carolina before entering the WNBA.
- 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: Marlies Triple: [Toronto Marlboros, alsoKnownAs, Marlies]
Generated description
Marlies is the common nickname for the Toronto Marlboros, a historic Canadian junior ice hockey team based in Toronto.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marlies Target entity description: Marlies is the common nickname for the Toronto Marlboros, a historic Canadian junior ice hockey team based in Toronto.
-
A.
Anneliese Bahr
Anneliese Bahr was the wife of German industrialist Alfried Krupp von Bohlen und Halbach, heir to the Krupp steel and armaments empire.
-
B.
Josephine Bruin
Josephine Bruin is one of the costumed bear mascots representing the University of California, Los Angeles at athletic events and campus activities.
-
C.
Dolly Haas
Dolly Haas was a German-born actress and singer known for her work in European cinema and later on Broadway and in American films.
-
D.
Jolanda
Jolanda is a feminine given name, commonly considered a variant of Yolanda, used in various European countries.
-
E.
Kamilla
Kamilla is a Brazilian professional basketball player known for her standout collegiate career at Syracuse and South Carolina before entering the WNBA.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a316ef48190831970ec914cf5a2 |
completed | March 20, 2026, 2:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfab992148190a1b1dfa33b971d11 |
completed | March 21, 2026, 1:56 a.m. |
| NEDg | Description generation | batch_69bdfb56021081909b23d22770bf3c88 |
completed | March 21, 2026, 1:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdfbf15f1481908b76bcdd37ebd4ce |
completed | March 21, 2026, 2:01 a.m. |
Created at: March 20, 2026, 1:13 p.m.