Triple
T25462661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australian Championships 1960 |
E638090
|
entity |
| Predicate | mixedDoublesRunnersUp |
P158566
|
FINISHED |
| Object |
Darlene Hard
Darlene Hard was an American tennis player and multiple Grand Slam champion renowned for her success in doubles during the 1950s and 1960s.
|
E1678486
|
NE FINISHED |
How this triple was built (3 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: Darlene Hard | Statement: [Australian Championships 1960, mixedDoublesRunnersUp, Darlene Hard]
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: Darlene Hard Triple: [Australian Championships 1960, mixedDoublesRunnersUp, Darlene Hard]
Generated description
Darlene Hard was an American tennis player and multiple Grand Slam champion renowned for her success in doubles during the 1950s and 1960s.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mixedDoublesRunnersUp Context triple: [Australian Championships 1960, mixedDoublesRunnersUp, Darlene Hard]
-
A.
mixedDoublesChampions
chosen
Indicates that the related entities together won a mixed doubles championship in a given event or competition.
-
B.
GrandTourDoubles
Indicates a competitive doubles tennis event or match that is part of a Grand Slam (Grand Tour) tournament series.
-
C.
hasMixedDoublesEquivalent
Indicates that one entity corresponds to or serves as the mixed doubles counterpart or equivalent of another entity.
-
D.
homeTeamRunnerUp
Indicates that the referenced team finished in second place (runner-up) in a competition held at its home venue or location.
-
E.
finishedRunnersUpIn
Indicates that one entity concluded a competition or contest in the runners-up position relative to another entity or event.
- F. None of above.
Provenance (6 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f72d0cc08190ba91a9dc39b1d848 |
completed | May 2, 2026, 1:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1089b4c3fc8190801d27a74bf721f2 |
completed | May 22, 2026, 4:52 p.m. |
| NEDg | Description generation | batch_6a108a67fc908190926977f4e65dba0b |
completed | May 22, 2026, 4:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a108afb4ad08190a1e9bcd731d98fcb |
completed | May 22, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 2:12 p.m.