Triple
T15537632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillermo Coria |
E370390
|
entity |
| Predicate | reachedWorldNo |
P119090
|
FINISHED |
| Object | 2 in ATP singles rankings |
—
|
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: 2 in ATP singles rankings | Statement: [Guillermo Coria, reachedWorldNo, 2 in ATP singles rankings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reachedWorldNo Context triple: [Guillermo Coria, reachedWorldNo, 2 in ATP singles rankings]
-
A.
reachedWorldNo3On
Indicates that an entity attained a world ranking of number 3 in a specified domain or ranking system at a particular time or event.
-
B.
hasWorldNumber
Indicates that an entity is associated with a specific world identified by a particular number.
-
C.
hasWorld
Indicates that an entity possesses, is associated with, or encompasses a particular world or global context.
-
D.
worldNumber
Indicates the specific world, dimension, or universe identifier associated with an entity or event.
-
E.
hasWorldCount
Indicates that an entity is associated with a specific number of worlds.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442f3c688190a599165e526af2ed |
completed | April 16, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69deda7a95c48190bbe29fadcf17191a |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f05f708190850f1d8782e132b0 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:06 a.m.