Triple
T20784963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Björn Borg |
E511604
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Ice Man
Ice Man is the cool-headed Swedish tennis legend Björn Borg, renowned for his calm demeanor and dominance at Wimbledon in the 1970s and early 1980s.
|
E1450318
|
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: Ice Man | Statement: [Björn Borg, nickname, Ice Man]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ice Man Context triple: [Björn Borg, nickname, Ice Man]
-
A.
Iceman
Iceman is a founding member of the X-Men with the mutant ability to generate and control ice and cold.
-
B.
Iceman
Iceman is the call sign of Tom Kazansky, a skilled and competitive U.S. Navy fighter pilot from the "Top Gun" film series.
-
C.
Iceman
Iceman is the nickname of Adam Vinatieri, the legendary NFL placekicker renowned for his clutch, game-winning field goals under extreme pressure.
-
D.
Iceman
Iceman is a 1984 science fiction drama film about the discovery and revival of a prehistoric man frozen in ice.
-
E.
Iceman
Iceman is a 2014 Hong Kong action-comedy film starring Donnie Yen as a Ming Dynasty warrior who time-travels to modern-day Hong Kong.
- 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: Ice Man Triple: [Björn Borg, nickname, Ice Man]
Generated description
Ice Man is the cool-headed Swedish tennis legend Björn Borg, renowned for his calm demeanor and dominance at Wimbledon in the 1970s and early 1980s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ice Man Target entity description: Ice Man is the cool-headed Swedish tennis legend Björn Borg, renowned for his calm demeanor and dominance at Wimbledon in the 1970s and early 1980s.
-
A.
Iceman
Iceman is the nickname of Adam Vinatieri, the legendary NFL placekicker renowned for his clutch, game-winning field goals under extreme pressure.
-
B.
Iceman
Iceman is a founding member of the X-Men with the mutant ability to generate and control ice and cold.
-
C.
Iceman
Iceman is the call sign of Tom Kazansky, a skilled and competitive U.S. Navy fighter pilot from the "Top Gun" film series.
-
D.
Iceman
Iceman is a 1984 science fiction drama film about the discovery and revival of a prehistoric man frozen in ice.
-
E.
Iceman
Iceman is a 2014 Hong Kong action-comedy film starring Donnie Yen as a Ming Dynasty warrior who time-travels to modern-day Hong Kong.
- 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_69e0b4cac7a48190a715cb3d545df2b4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c28b4ce88190a45f1c99b58d18eb |
completed | April 21, 2026, 12:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08ef9bcc6c8190a594a7c083cca572 |
completed | May 16, 2026, 10:28 p.m. |
| NEDg | Description generation | batch_6a08f36a492481908518eba744452df0 |
completed | May 16, 2026, 10:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08f43e36588190a556a19b9dbb738b |
completed | May 16, 2026, 10:48 p.m. |
Created at: April 16, 2026, 12:38 p.m.