Triple
T4377071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gothia Cup |
E99032
|
entity |
| Predicate | matchCount |
P42152
|
FINISHED |
| Object | over 4000 matches in some years |
—
|
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: over 4000 matches in some years | Statement: [Gothia Cup, matchCount, over 4000 matches in some years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchCount Context triple: [Gothia Cup, matchCount, over 4000 matches in some years]
-
A.
matchResult
Indicates the outcome or final status produced by a particular match or game between participants.
-
B.
matchType
Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
-
C.
matches
Indicates that two entities correspond to or are in agreement with each other according to some defined criteria or pattern.
-
D.
matchContext
Indicates that two or more entities are related within the same situational, conversational, or environmental setting that frames or influences their interaction.
-
E.
numberOfCounts
chosen
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3523ed220819090cef1a7933489d9 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:18 p.m.