Triple
T1393687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 Commonwealth Games |
E30616
|
entity |
| Predicate | hostNationMedalsTotal |
P14576
|
FINISHED |
| Object | 53 |
—
|
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: 53 | Statement: [2014 Commonwealth Games, hostNationMedalsTotal, 53]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostNationMedalsTotal Context triple: [2014 Commonwealth Games, hostNationMedalsTotal, 53]
-
A.
hostNationTotalMedals
chosen
Indicates the total number of medals won by the nation hosting a given sporting event or competition.
-
B.
hostNationMedalRank
Indicates the ranking position of the host nation in the overall medal standings for a sporting event or multi-sport competition.
-
C.
hostNationGoldMedals
Indicates the number of gold medals won by the nation hosting a particular event or competition.
-
D.
hostNationCapital
Indicates that a city serves as the capital of a particular host nation.
-
E.
topMedalCountry
Indicates that a country is the one with the highest total medal count (or ranking) in a given competition 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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c37cd99081908d16014e0b99992d |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4bf017f8081908572121560ec621f |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.