Triple
T29447673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 6 Hours of Monza |
E746893
|
entity |
| Predicate | typicalSeries |
P14858
|
FINISHED |
| Object | FIA World Endurance Championship |
E204389
|
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: FIA World Endurance Championship | Statement: [6 Hours of Monza, typicalSeries, FIA World Endurance Championship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSeries Context triple: [6 Hours of Monza, typicalSeries, FIA World Endurance Championship]
-
A.
typicalSeriesFormat
Indicates that one entity represents the usual or standard format or structure in which a given series is presented or organized.
-
B.
seriesOf
Indicates that one entity is a sequence or ordered set of related items, events, or parts that collectively form or belong to another entity.
-
C.
seriesType
chosen
Indicates the classification or category of a series that an entity belongs to or is associated with.
-
D.
narrativeSeries
Indicates that one narrative work belongs to, or is part of, an ordered series of related narratives.
-
E.
mainSeries
Indicates that one creative work is the primary or canonical series to which another related work (such as a spin-off, side story, or adaptation) belongs.
- F. None of above.
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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a01beacf8a88190ac643a75c7a0efc4 |
completed | May 11, 2026, 11:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a25d93d37908190b2314a1488b66e3e |
completed | June 7, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_6a01be152c8c8190bb19d64a683e2aae |
completed | May 11, 2026, 11:31 a.m. |
Created at: April 28, 2026, 3:29 p.m.