Triple
T15922503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Walloon Arrow |
E386125
|
entity |
| Predicate | womenEditionInstanceOf |
P65043
|
FINISHED |
| Object | women's road cycling race |
—
|
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: women's road cycling race | Statement: [The Walloon Arrow, womenEditionInstanceOf, women's road cycling race]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenEditionInstanceOf Context triple: [The Walloon Arrow, womenEditionInstanceOf, women's road cycling race]
-
A.
womenEdition
chosen
Indicates that something is a version, issue, or release specifically tailored for or dedicated to women.
-
B.
womenSection
Indicates that something is designated as belonging to, located in, or associated with the women's section or area.
-
C.
viewOnWomen
Indicates a person's attitudes, beliefs, or perspectives regarding women and gender roles.
-
D.
femaleFeature
Indicates that the subject possesses a characteristic or attribute that is typically associated with females.
-
E.
womenStatus
Indicates the social, legal, economic, or cultural position or condition assigned to women within a given context or system.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.