Triple
T11176711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Rugby Women’s Sevens Series |
E264430
|
entity |
| Predicate | matchHalfLength |
P98271
|
FINISHED |
| Object | 7 minutes |
—
|
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: 7 minutes | Statement: [World Rugby Women’s Sevens Series, matchHalfLength, 7 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchHalfLength Context triple: [World Rugby Women’s Sevens Series, matchHalfLength, 7 minutes]
-
A.
halvesPerMatch
Indicates the number of distinct halves into which each match is divided.
-
B.
isInHalf
Indicates that one entity is located within or belongs to a specified half or subdivision of another entity.
-
C.
matchLevel
Indicates the degree or extent to which two entities correspond, align, or are compatible with each other.
-
D.
matchRatio
Indicates the degree of similarity or correspondence between two items, typically expressed as a numerical ratio or percentage.
-
E.
matchOf
Indicates that one entity is a specific match, counterpart, or corresponding instance of another entity within a defined context or set.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8987e1081909b28a0bdb866beae |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cf0e6e88190973694abe2990973 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d7706116248190a87440bec3960884 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.