Triple
T419116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1974 FIFA World Cup |
E8060
|
entity |
| Predicate | numberOfHostCities |
P14674
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [1974 FIFA World Cup, numberOfHostCities, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHostCities Context triple: [1974 FIFA World Cup, numberOfHostCities, 9]
-
A.
hasCoHostCity
Indicates that an event is jointly hosted or organized by the specified city alongside one or more other cities.
-
B.
hasHostCity
Indicates that a particular event, organization, or activity is located in or officially hosted by a specific city.
-
C.
olympicHostCountry
Indicates that a country served as the official host nation for a particular edition of the Olympic Games.
-
D.
hasParticipantCity
Indicates that a city is involved as a participant in an event, activity, or relationship.
-
E.
servesAsFocusCityFor
Indicates that a city functions as a primary or designated focus city for an airline, organization, or transportation network, typically hosting significant but not hub-level operations or activities.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd3b948819097d96c73d0a0f699 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb8545c8190a2b8517e7ed5b92e |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.