Triple
T3437913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivy League women's tennis |
E72498
|
entity |
| Predicate | includesDoublesMatches |
P1393
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Ivy League women's tennis, includesDoublesMatches, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesDoublesMatches Context triple: [Ivy League women's tennis, includesDoublesMatches, yes]
-
A.
includesMatch
Indicates that one entity contains or encompasses a particular match or matching instance of another entity.
-
B.
usesMatchesFrom
Indicates that one entity relies on or incorporates matches (e.g., pattern matches, rule matches, or result matches) produced by another entity or process.
-
C.
includesClause
Indicates that one entity (typically a document, contract, or statement) contains or incorporates a specific clause as part of its content.
-
D.
includedWith
Indicates that one entity is provided or packaged together as part of another entity.
-
E.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
- F. None of above.
Provenance (3 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_69ad85af50288190a854b76653deee6f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9f575cc8190866929b1e8930143 |
completed | March 8, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69adae00ad588190bef24373b58a2e1a |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:16 p.m.