Triple
T3580355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillermo Coria |
E75783
|
entity |
| Predicate | ATPMasters1000Titles |
P49847
|
FINISHED |
| Object | Hamburg Masters champion |
—
|
LITERAL FINISHED |
How this triple was built (2 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: Hamburg Masters champion | Statement: [Guillermo Coria, ATPMasters1000Titles, Hamburg Masters champion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ATPMasters1000Titles Context triple: [Guillermo Coria, ATPMasters1000Titles, Hamburg Masters champion]
-
A.
majorChampionshipWins
Indicates the number of major championship titles an entity has won.
-
B.
formerWorldNo1
Indicates that the subject was ranked number one in the world in the past, but does not hold that top ranking currently.
-
C.
GrandSlams
Indicates that an entity has won or is associated with victories in major Grand Slam tournaments within a given sport.
-
D.
grandSlamSinglesTitles
Indicates the number of Grand Slam singles tennis titles an entity has won.
-
E.
grandSlamOrder
Indicates that one event or achievement in a sequence is a grand slam and specifies its relative order or position among other such events.
- F. None of above. chosen
Provenance (4 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0ffecdc8190bf01c8ba90e3733e |
completed | March 8, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb8e4ba948190a9b777cf7f788b96 |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:21 p.m.