Triple

T28693076
Position Surface form Disambiguated ID Type / Status
Subject US Open mixed doubles E729337 entity
Predicate playedOn P21420 FINISHED
Object Laykold hard courts (current)
Laykold hard courts (current) are the modern acrylic hard-court surfaces used at the US Open, known for their medium-fast pace and durability in professional tennis competition.
E1829630 NE 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: Laykold hard courts (current) | Statement: [US Open mixed doubles, playedOn, Laykold hard courts (current)]
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: Laykold hard courts (current)
Triple: [US Open mixed doubles, playedOn, Laykold hard courts (current)]
Generated description
Laykold hard courts (current) are the modern acrylic hard-court surfaces used at the US Open, known for their medium-fast pace and durability in professional tennis competition.

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_69f043e60b6c8190ac2cd042e77fe6e9 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f656acbcd08190b7519a0203609fab completed May 2, 2026, 7:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc3b235108190bdac7f5906d670df completed May 31, 2026, 11:26 p.m.
NEDg Description generation batch_6a1cc44b6ac081909cd782a2b589b6f5 completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc544e60081908682c3750e6ac83d completed May 31, 2026, 11:33 p.m.
Created at: April 28, 2026, 5:37 a.m.